System and method for vehicle propulsion control

Abstract

A method for controlling propulsion of a vehicle is provided. The method comprises: identifying at least one route characteristic of a portion of a most likely path; determining a vehicle energy consumption profile for the vehicle based at least on historical data indicative of energy consumption of the vehicle for at least a portion of a route previously traversed by the vehicle, the at least a portion of the route having at least one route characteristic corresponding to the at least one route characteristic of the portion of the most probable path; and determining a route energy consumption profile for the most probable path based on the at least one route characteristic of the portion of the most probable path and the vehicle energy consumption profile. The method further includes determining a target vehicle speed profile based on the at least one route characteristic and the vehicle energy consumption profile; and selectively controlling vehicle propulsion based on the target vehicle speed profile.

Description

Government licensing rights

[0001] This invention was made with Government support under Contract DE-AR0000794 awarded by the Advanced Research Projects Agency-Energy (ARPA-E). The Government has certain rights in this invention. Technical Field

[0002] The present disclosure relates to vehicle energy usage, and more particularly to systems and methods for estimating the remaining range of a vehicle and reducing driver range anxiety. Background Art

[0003] Vehicles (such as cars, trucks, sport utility vehicles, cross-overs, minivans, or other suitable vehicles) increasingly rely on batteries to provide energy for the vehicle propulsion system (e.g., as in the case of electric vehicles that use one or more electric motors to provide propulsion or hybrid vehicles that use one or more electric motors and an internal combustion engine to provide propulsion).

[0004] In such vehicles, it may be difficult to accurately predict the remaining distance that the vehicle can travel using the remaining battery charge or energy of one or more vehicle batteries of the vehicle (e.g., the remaining distance may be referred to as range). This may cause operator anxiety because it may be inconvenient, difficult, or impossible to charge the vehicle batteries before the vehicle reaches a desired destination. Furthermore, the difficulty in accurately predicting the remaining distance that the vehicle can travel using the remaining battery charge or energy of one or more vehicle batteries may deter potential vehicle purchasers from purchasing an electric vehicle or a hybrid vehicle. Summary of the invention

[0005] The present disclosure generally relates to vehicle propulsion control systems and methods.

[0006] One aspect of the disclosed embodiment includes a method for controlling vehicle propulsion. The method includes: identifying at least one route characteristic of a portion of a most likely path; determining a vehicle energy consumption profile for the vehicle based at least on historical data indicating energy consumption of the vehicle for at least a portion of a route previously traversed by the vehicle, the at least a portion of the route having at least one route characteristic corresponding to at least one route characteristic of a portion of the most likely path; and determining a route energy consumption profile for the most likely path based on the at least one route characteristic of the portion of the most likely path and the vehicle energy consumption profile. The method also includes: determining a target vehicle speed profile based on the at least one route characteristic and the vehicle energy consumption profile; and selectively controlling vehicle propulsion based on the target vehicle speed profile.

[0007] Another aspect of the disclosed embodiment includes a system for controlling vehicle propulsion. The system includes a processor and a memory. The memory includes instructions that, when executed by the processor, cause the processor to: identify at least one route characteristic of a portion of a most likely path; determine a vehicle energy consumption profile for the vehicle based at least on historical data indicating energy consumption of the vehicle for at least a portion of a route previously traversed by the vehicle, the at least a portion of the route having at least one route characteristic corresponding to at least one route characteristic of a portion of the most likely path; determine a route energy consumption profile for the most likely path based on at least one route characteristic of a portion of the most likely path and the vehicle energy consumption profile; determine a target vehicle speed profile based on the at least one route characteristic and the vehicle energy consumption profile; and selectively control vehicle propulsion based on the target vehicle speed profile.

[0008] Another aspect of the disclosed embodiment includes a non-transitory computer-readable storage medium including executable instructions that, when executed by a processor, facilitates performance of operations including: identifying at least one route characteristic of a portion of a most likely path; determining a vehicle energy consumption profile for a vehicle based at least on historical data indicating energy consumption of the vehicle for at least a portion of a route previously traversed by the vehicle, the at least a portion of the route having at least one route characteristic that corresponds to at least one route characteristic of a portion of the most likely path; determining a current state of charge of a vehicle battery of the vehicle; determining a current state of charge of a vehicle battery of the vehicle based on historical data; determining a current state of charge of a vehicle battery of the vehicle ... Based on at least one route characteristic and a vehicle energy consumption profile of a portion of a most likely path, determining a route energy consumption profile for the most likely path; calculating an estimated remaining charge of the vehicle battery at an end point of the most likely path based on the charge state of the vehicle battery and the route energy consumption profile; determining whether the estimated remaining charge of the vehicle battery is within the vehicle battery charge range; in response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range, performing the following operations: determining a target vehicle speed profile based on at least one route characteristic, the vehicle energy consumption profile and the charge state of the vehicle battery; and generating an indication; and providing the indication.

[0009] These and other aspects of the disclosure are provided in the following detailed description of the embodiments, the appended claims and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The present disclosure is best understood from the following detailed description when read in conjunction with the accompanying drawings. It is emphasized that, according to common practice, the various features of the drawings are not to scale. Instead, the sizes of the various features are arbitrarily expanded or reduced for clarity.

[0011] Figure 1 A vehicle in accordance with the principles of the present disclosure is generally illustrated.

[0012] Figure 2 A block diagram of a vehicle propulsion control system in accordance with the principles of the present disclosure is generally illustrated.

[0013] Figure 3 is a flow chart generally illustrating an energy consumption method according to the principles of the present disclosure.

[0014] Figure 4 The diagram generally illustrates the estimation of energy consumption in a vehicle battery for a future trip using machine learning in accordance with the principles of the present disclosure.

[0015] Figure 5 is a flow chart generally illustrating a vehicle propulsion control method according to the principles of the present disclosure.

[0016] Figure 6 is a flow chart generally illustrating an alternative vehicle propulsion control method according to the principles of the present disclosure.

[0017] Figure 7 is a flow chart generally illustrating an alternative vehicle propulsion control method according to the principles of the present disclosure.

[0018] Figure 8 is a flow chart generally illustrating a remaining vehicle battery range estimation method according to the principles of the present disclosure.

[0019] Fig. 9 is a flow chart generally illustrating an alternative remaining vehicle battery range estimation method according to the principles of the present disclosure.

[0020] Fig.10 is a flow chart generally illustrating an alternative remaining vehicle battery range estimation method according to the principles of the present disclosure.

[0021] Fig.11 is a flow chart generally illustrating an alternative remaining vehicle battery range estimation method according to the principles of the present disclosure.

[0022] Fig.12 is a flow chart generally illustrating a vehicle propulsion control method according to the principles of the present disclosure. DETAILED DESCRIPTION

[0023] The following discussion relates to various embodiments of the present invention. Although one or more of these embodiments may be preferred, the disclosed embodiments should not be interpreted or otherwise used as limitations on the scope of the present disclosure, including the claims. In addition, it will be understood by those skilled in the art that the following description has broad application, and the discussion of any embodiment is intended only to be an example of that embodiment, and is not intended to imply that the scope of the present disclosure, including the claims, is limited to that embodiment.

[0024] As described, vehicles (such as cars, trucks, sport utility vehicles, crossovers, minivans, or other suitable vehicles) increasingly rely on batteries to provide energy for the vehicle propulsion system (e.g., in the case of electric vehicles that use one or more electric motors to provide propulsion or hybrid vehicles that use one or more electric motors and an internal combustion engine to provide propulsion).

[0025] In such vehicles, it may be difficult to accurately predict the remaining distance that the vehicle can travel using the remaining battery life or charge of one or more vehicle batteries of the vehicle (e.g., the remaining distance may be referred to as range). This may cause operator anxiety (e.g., which may be referred to as range anxiety) because it may be inconvenient, difficult, or impossible to charge the vehicle batteries before the vehicle reaches a desired destination. Furthermore, the difficulty in accurately predicting the remaining distance that the vehicle can travel using the remaining battery life or charge of one or more vehicle batteries may deter potential vehicle buyers from purchasing an electric vehicle or a hybrid vehicle.

[0026] Range anxiety is one of the major challenges hindering the widespread adoption of electric vehicles (EVs). The psychological fear among EV owners is that the vehicle may not have enough energy to cover the distance to the intended destination and that the vehicle may be stranded before reaching the destination. While this was especially true in the early stages of EV development when the batteries used in EVs had limited capacity, many consumers still believe this to be the case even now that higher capacity batteries are available. The issue of insufficient battery capacity that used to be a common concern has now been replaced by a lack of confidence in the estimated range displayed on the vehicle's dashboard. According to recent literature, most EV drivers typically retain about 30% of the estimated range on the dashboard due to a lack of trust in the accuracy of the remaining driving range (RDR) estimate.

[0027] Therefore, systems and methods such as those described herein that are configured to provide accurate predictions of the RDR of a vehicle based on the current state of charge of at least one vehicle battery may be desirable. In some embodiments, the systems and methods described herein may be configured to provide accurate estimates of the RDR in EV, hybrid vehicles, and / or internal combustion vehicles by predicting future energy consumption of a trip based on comprehensive driving conditions (e.g., comprehensive driving conditions may include information about route characteristics, traffic conditions, vehicle operation, driving style, environmental impacts, etc.).

[0028] The systems and methods described herein may be configured to convert such information into energy consumption in an energy storage system (ESS) (e.g., such as a battery or other suitable energy storage system). The systems and methods described herein may be configured to determine the energy consumption of a vehicle for a particular route based on driving style recognition, speed profile prediction, and energy consumption from one or more wheels of the vehicle to the ESS. The systems and methods described herein may be configured to combine a model-based approach with a data-driven approach, which may be applied to all electric vehicle platforms, regardless of the type of ESS.

[0029] The systems and methods described herein may be configured to calculate the RDR using equation (1).

[0030] The systems and methods contemplated herein can be configured to support accurate determination of the RDR by determining a reliable estimate of future energy consumption (e.g., the denominator in equation (1)). The systems and methods contemplated herein can be configured to reduce or alleviate range anxiety and reduce the amount of energy that a driver intentionally retains in an ESS due to uncertainty about the RDR, which is equivalent to increasing the available energy capacity.

[0031] Mileage estimation methods can be classified into historical methods, model-based methods, and data-driven or machine learning (ML) methods. Historical methods may be relatively unreliable because they rely on the assumption that future energy consumption will be similar to past energy consumption. Model-based methods generally focus on establishing a driving profile over time by considering factors such as route information, speed regulations, driving behavior, and / or the like to predict the future speed profile (e.g., acceleration, deceleration, average speed, and / or the like) of a vehicle. Model-based estimates are generally more accurate than historical methods, but may also be computationally intensive when using detailed models to represent the energy consumption of a vehicle. ML can utilize relatively large data sets to generate and develop algorithms that can learn complex relationships between different features of data and ultimately make credible predictions during deployment. The systems and methods contemplated herein may be configured to combine model-based methods with ML to provide reliable mileage estimates without requiring significant computing power.

[0032] Most range estimation algorithms fail to address the problem of real-time range estimation and do not take into account environmental and driver behavior factors, which may result in relatively large variations in energy consumption for a given trip or route. Thus, the systems and methods contemplated herein may be configured to predict energy consumption for a future trip or route using route characteristics, traffic conditions, vehicle operation, driving style, environmental influences, and / or other suitable characteristics or aspects of the vehicle, operator, route, traffic, and / or environment.

[0033] In some embodiments, the systems and methods contemplated herein may be configured to convert the above information into energy consumption in an ESS, such as Figure 3 200 as a whole (e.g., the above information includes driving style identification, speed profile prediction, and energy consumption from wheels to ESS). For example, at 202, method 200 may identify a driving style based on one or more driving characteristics (e.g., which may include one or more measurements). The systems and methods described herein may be configured to analyze driving behavior to store data in a driver profile, which may be used for prediction of a speed profile or for alerts related to energy conservation. Driving characteristics may include instantaneous speed, pedal position (e.g., acceleration and braking), distance to a stop sign, distance to a speed limit charge, speed limit offset, any other suitable driving characteristics, or a combination thereof. The systems and methods described herein may be configured to determine driving style parameters related to aggressiveness used in speed profile prediction based on driving characteristics. For example, an increase in aggressive driving may result in a decrease in energy efficiency, while an increase in conservative driving may have the opposite effect, which may have an impact on the PDR of the vehicle.

[0034] At 204, method 200 uses a physics-based model to predict a speed profile. The systems and methods described herein may be configured to predict a speed profile for a route using route information, traffic conditions, and / or driving style parameters. The systems and methods described herein may be configured to extract route features from a map or navigation system that may provide information about road type, distance between coordinates, elevation and / or slope, speed limits, stop sign (SS) locations, traffic light (TL) locations, alternative routes, locations of charging / refill stations on the route, and the like. The systems and methods described herein may be configured to collect traffic information for both historical traffic patterns and real-time traffic conditions.

[0035] The systems and methods described herein can be configured to use historical data as stochastic behavior trends while using real-time data as deterministic (e.g., the systems and methods described herein can be retrieved and updated in real-time or substantially real-time, or in any other suitable time period). For example, the systems and methods described herein can be configured to randomly define the color of a traffic light at the beginning of a route, and retrieve the current flow speed of a particular road segment in real-time using a navigation system associated with a vehicle or associated with a computing device. The systems and methods described herein can be configured to generate or predict a speed profile based on route and traffic information and the information generated at 202 using an enhanced driver model (EDM).

[0036] At 206, method 200 uses a physics-based model and a road load equation to analyze segment energy usage. For example, the systems and methods described herein may be configured to use an ML approach or a stochastic approach to determine the battery energy consumption of a predicted speed profile. A route may consist of separate segments. The systems and methods described herein may be configured to use the information generated at 202 and 204 to identify the speed profile and lift profile of each segment. The systems and methods described herein may be configured to use a physics-based model to determine the energy to overcome aerodynamic drag, rolling resistance, and / or slope at one or more wheels of a vehicle and the energy to accelerate and decelerate on a given segment using a road load equation and vehicle parameters.

[0037] At 208 , method 200 provides an energy description for each segment as input to a ML model (e.g., the ML model may include an ML regression model) along with additional information such as segment length, expected travel time on the segment, battery state of charge (SoC) at the start of the segment, environmental conditions on the segment, and / or any other suitable characteristics (e.g., based on the specific vehicle application and available information).

[0038] In some embodiments, the ML model can be trained to predict the segment battery energy consumption and expected SoC at the end of the segment given the segment input features. The ML model can be used recursively to estimate the battery energy consumption of each segment on the route, such as in Figure 4 250 in FIG. The systems and methods described herein may be configured to add together the estimated battery energy consumption for all segments to determine the total battery energy consumption for the remaining route. As the vehicle travels along the route, the systems and methods described herein may be configured to update the battery energy consumption for the remaining route (e.g., at any suitable interval or period) using updated traffic information, environmental conditions, and based on the latest vehicle operating conditions.

[0039] In some embodiments, the systems and methods described herein can be configured to reduce or eliminate driver anxiety by selectively controlling propulsion of a vehicle according to a target speed profile or by providing a driver with a recommendation for achieving a target speed profile. As described herein, a target speed profile can be configured to achieve optimal energy consumption of a vehicle along a route, which can increase the likelihood that the vehicle reaches a destination before the vehicle battery is depleted.

[0040] The systems and methods described herein may be configured to: use a comprehensive set of route characteristics of a route to a driver-defined destination to determine an optimized speed profile based on a driver-defined remaining battery SoC when the vehicle arrives at the destination, thereby reducing or eliminating range anxiety for drivers of battery EVs. The systems and methods described herein may be configured to: allow the driver to trade off remaining SoC at the destination with travel time to the destination; provide updated end-of-trip SoC estimates and speed profiles during a trip based on unexpected events along the route; allow the driver to update the desired destination SoC during a trip; and / or warn the driver when the desired destination SoC is not achievable.

[0041] The systems and methods described herein can be configured to reduce the driver's range anxiety by enabling the driver to use one of various propulsion functions such as adaptive cruise control and a target vehicle speed generated by an optimized target speed. The driver can use a human-machine interface (HMI) to provide driver settings, which include at least: a desired destination; a desired minimum destination SoC; a value indicating a preferred trade-off between energy efficiency and travel time (e.g., an "aggressiveness factor"); a minimum and maximum value of a speed band around a speed limit acceptable to the driver; and / or any other suitable information. The systems and methods described herein can be configured to determine an appropriate route to a destination, and based on the defined route, obtain a set of characteristics of the route, which can include static route characteristics and / or dynamic route characteristics. Static route characteristics can include: route and terrain (e.g., route distance, road type, elevation, and / or any other suitable characteristics); vehicle and battery characteristics (e.g., aerodynamic drag coefficient, rolling resistance, battery capacity, and / or any other suitable characteristics); environmental characteristics (e.g., time of day and / or any other suitable characteristics); and / or driving behavior characteristics (e.g., maximum acceleration / deceleration and / or any other suitable characteristics). Dynamic route characteristics may include: route and terrain characteristics (e.g., traffic regulations (such as speed limits), traffic light, and / or stop sign locations, traffic density, vehicle location, and / or any other suitable characteristics); vehicle and battery characteristics (e.g., vehicle mass, battery SoC, battery temperature, HVAC settings, and / or any other suitable characteristics); environmental characteristics (e.g., temperature, rainfall, wind speed and direction, and / or any other suitable characteristics); and / or driving behavior characteristics (e.g., driver aggressiveness, and / or any other suitable characteristics).

[0042] Based on route characteristics and driver settings, the systems and methods described herein can be configured to determine if there is an optimal target speed profile that results in a destination SoC that is greater than or equal to the minimum destination SoC. Static route characteristics may include: route and terrain (e.g., route distance, road type, elevation, and / or any other suitable characteristics); vehicle and battery characteristics (e.g., aerodynamic drag coefficient, rolling resistance, battery capacity, and / or any other suitable characteristics); environmental characteristics (e.g., time of day and / or any other suitable characteristics); and / or driving behavior characteristics (e.g., maximum acceleration / deceleration and / or any other suitable characteristics). Dynamic route characteristics may include: route and terrain characteristics (e.g., traffic regulations (such as speed limits), traffic lights, and / or stop sign locations, traffic density, vehicle location, and / or any other suitable characteristics); vehicle and battery characteristics (e.g., vehicle mass, battery SoC, battery temperature, HVAC settings, and / or any other suitable characteristics); environmental characteristics (e.g., temperature, rainfall, wind speed and direction, and / or any other suitable characteristics); and / or driving behavior characteristics (e.g., driver aggressiveness, and / or any other suitable characteristics).

[0043] If there is an optimal target speed profile solution that satisfies the driver's settings, the systems and methods described herein can be configured to prompt the driver (e.g., using an HMI or other suitable display or interaction mechanism) to engage adaptive cruise control. The systems and methods described herein can be configured to set the adaptive cruise control speed based on the optimal target speed profile. Along the route, the systems and methods described herein can be configured to recalculate the estimated destination SoC based on updated route characteristics. If at any point along the route, the estimated destination SoC becomes lower than the driver's desired minimum destination SoC by more than a definable threshold, the systems and methods described herein can be configured to: determine a new optimal target speed profile to the destination, and, assuming a solution exists, replace the previous target speed profile with the updated optimal target speed profile.

[0044] If an optimal target speed profile solution cannot be determined at any point along the route (e.g., no feasible solution exists for the given route characteristics and driver settings), the systems and methods described herein can be configured to: determine a set of potential charging locations; present the potential charging locations to the driver; and allow the driver to select among the potential charging stations. Based on the driver selection, the systems and methods described herein can be configured to operate the vehicle as described to reach the charging point location, and will indicate the minimum charge required to achieve a feasible solution for the optimal target speed profile within the constraints set by the driver. Once the vehicle is charged, the systems and methods described herein can be configured to subsequently operate the vehicle as described to reach the final driver destination.

[0045] In some embodiments, the systems and methods described herein may be configured to: if it is determined that the vehicle should stop and charge to reach a destination (eg, within constraints set by the driver), optimize the charging profile within the constraints set by the driver to minimize battery aging.

[0046] In some embodiments, the systems and methods described herein can be configured to adapt the amount of power in the driver's settings as the vehicle traverses a route. In some embodiments, the systems and methods described herein can be configured to consider predicted HVAC settings (e.g., and energy usage through the end of the trip) in addition to or as an alternative to using current HVAC settings, which predicted HVAC settings can be based on learned driver HVAC history.

[0047] In some embodiments, the systems and methods described herein may be configured to use the expected remaining range at a destination provided by the driver in addition to or as an alternative to the driver providing the expected SoC at the destination. In some embodiments, the systems and methods described herein may be configured to receive multiple destinations (e.g., a final destination, and intermediate, waypoint destinations) via driver settings. Additionally or alternatively, the systems and methods described herein may be configured to request the driver to input a home location as well as home charging availability to consider home destination charging opportunities.

[0048] In some embodiments, the systems and methods described herein may be configured to take into account prices at different charging locations as part of determining an appropriate charging location when a trip must be completed. In some embodiments, the systems and methods described herein may be configured to allow the driver to input a desired arrival time at a final destination (e.g., in addition to or as an alternative to a final destination SoC), and, if applicable, provide a desired driving aggressiveness for an optimized driving profile and predicted final SoC.

[0049] In some embodiments, the systems and methods described herein may be configured to suggest remaining range and charging points based on the availability of charging stations. For example, a driver may indicate a desire to have 50 miles of remaining range when the vehicle arrives at the desired destination. If the systems and methods described herein determine that the closest charging station to the destination is 70 miles away, the systems and methods described herein may be configured to suggest 70 miles as the remaining range when the vehicle arrives at the desired destination.

[0050] In some embodiments, the systems and methods described herein may be configured to determine one or more route characteristics associated with a most probable path identified by a navigation system using most probable path information of the navigation system in response to the driver not entering a destination.

[0051] In some embodiments, the systems and methods described herein may be configured to identify at least one route characteristic of a portion of a selected route. The systems and methods described herein may be configured to determine a vehicle energy consumption profile for a vehicle based at least on historical data indicating energy consumption of the vehicle for at least a portion of a route previously traversed by the vehicle, the at least a portion of the route having at least one route characteristic corresponding to at least one route characteristic of a portion of the selected route. The systems and methods described herein may be configured to determine a current state of charge of a vehicle battery of a vehicle.

[0052] The systems and methods described herein may be configured to determine a route energy consumption profile for a selected route based on at least one route characteristic of a portion of the selected route and a vehicle energy consumption profile (e.g., the route energy consumption profile may represent predicted energy usage for the route). The systems and methods described herein may be configured to calculate an estimated remaining charge of a vehicle battery at the end of a selected route based on the charge state of the vehicle battery and the route energy consumption profile. The systems and methods described herein may be configured to determine whether the estimated remaining charge of the vehicle battery is within the vehicle battery charge range (e.g., the vehicle battery charge range may represent an acceptable mileage for continuing along the route). The systems and methods described herein may be configured to generate a first indication in response to determining that the estimated remaining charge is within the vehicle battery charge range. The first indication may include an estimated remaining charge of the vehicle battery at the end of the selected route.

[0053] The systems and methods described herein may be configured to generate a second indication in response to determining that the estimated remaining power is less than a lower limit of the vehicle battery power range. The second indication may include a warning indicating that the vehicle battery may be exhausted before the vehicle reaches the end of the selected route. The systems and methods described herein may be configured to provide one of the first indication and the second indication (e.g., based on a determination result of whether the remaining power of the vehicle battery is within the vehicle battery power range). For example, the systems and methods described herein may be configured to provide a first indication and / or a second indication at a display of a vehicle, at a mobile computing device, to an autonomous controller of a vehicle, etc.

[0054] In some embodiments, the systems and methods described herein may be configured to determine a target vehicle speed profile and generate a second indication based on at least one route characteristic, a vehicle energy consumption profile, and a state of charge of a vehicle battery in response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range. The second indication may further include a recommendation to follow the target vehicle speed profile to avoid exhausting the vehicle battery before the vehicle reaches the end of the selected route. The systems and methods described herein may be configured to control propulsion of a vehicle based on the target vehicle speed profile and / or by providing a recommendation to an operator of the vehicle to achieve the target vehicle speed profile.

[0055] Figure 1A vehicle 10 according to the principles of the present disclosure is generally illustrated. The vehicle 10 may include any suitable vehicle, such as a car, truck, sport utility vehicle, minivan, crossover, any other passenger vehicle, any suitable commercial vehicle, or any other suitable vehicle. Although the vehicle 10 is shown as a passenger vehicle with wheels and for use on the road, the principles of the present disclosure may be applied to other vehicles, such as airplanes, ships, trains, drones, or other suitable vehicles. The vehicle 10 includes a vehicle body 12 and a hood 14. A portion of the vehicle body 12 defines a passenger compartment 18. Another portion of the vehicle body 12 defines an engine compartment 20. The hood 14 may be movably attached to a portion of the vehicle body 12 so that the hood 14 provides access to the engine compartment 20 when the hood 14 is in a first position or an open position, and covers the engine compartment 20 when the hood 14 is in a second position or a closed position.

[0056] The passenger compartment 18 is disposed behind the engine compartment 20. The vehicle 10 may include any suitable propulsion system (including an internal combustion engine, one or more electric motors (e.g., electric vehicles), one or more fuel cells), a hybrid (e.g., hybrid vehicle) propulsion system including a combination of an internal combustion engine, one or more electric motors, and / or any other suitable propulsion system. In some embodiments, the vehicle 10 may include a petrol or gasoline fuel engine, such as a spark ignition engine. In some embodiments, the vehicle 10 may include a diesel fuel engine, such as a compression ignition engine. The engine compartment 20 accommodates and / or encloses at least some components of the propulsion system of the vehicle 10. Additionally or alternatively, propulsion controls such as an accelerator actuator (e.g., an accelerator pedal), a brake actuator (e.g., a brake pedal), a steering wheel, and other such components are disposed in the passenger compartment 18 of the vehicle 10. The propulsion controls may be actuated or controlled by a driver of the vehicle 10 and may be directly connected to corresponding components of the propulsion system, such as a throttle, brakes, vehicle axles, vehicle transmission, etc. In some embodiments, the propulsion controls may transmit signals to a vehicle computer (e.g., driven by wires), which in turn may control corresponding propulsion components of the propulsion system.

[0057] In some embodiments, the vehicle 10 includes a transmission that is connected to the crankshaft via a flywheel or a clutch or a fluid coupling. In some embodiments, the transmission includes a manual transmission. In some embodiments, the transmission includes an automatic transmission. In the case of an internal combustion engine or a hybrid vehicle, the vehicle 10 may include one or more pistons that operate in cooperation with the crankshaft to generate a force that is translated to one or more axles that rotate the wheel 22 through the transmission. When the vehicle 10 includes one or more motors, the vehicle battery and / or fuel cell provide energy to the motor to rotate the wheel 22. In the case where the vehicle 10 includes a vehicle battery for providing energy to one or more motors, when the battery is exhausted, the battery can be connected to the power grid (e.g., using a wall socket) to recharge the battery unit. Additionally or alternatively, the vehicle 10 can adopt regenerative braking, which uses one or more motors of the vehicle 10 as a generator for converting the kinetic energy lost due to deceleration back to the energy stored in the battery.

[0058] The vehicle 10 may include an automatic vehicle propulsion system, such as cruise control, adaptive cruise control, automatic braking control, other automatic vehicle propulsion systems, or combinations thereof. The vehicle 10 may be an autonomous or semi-autonomous vehicle, or other suitable type of vehicle. The vehicle 10 may include more or fewer features than those generally illustrated and / or disclosed herein.

[0059] Figure 2 Generally, a block diagram of a vehicle propulsion control system 100 according to the principles of the present disclosure is shown. The system 100 can be disposed within a vehicle such as the vehicle 10. The system 100 is configured to selectively control propulsion of the vehicle 10, and in some embodiments, the system 100 is configured to determine a profile of a target vehicle speed and / or a target vehicle torque distribution based on various input information (e.g., route information, vehicle characteristic information, traffic information, other suitable information, or a combination thereof). The profile of the target vehicle speed and / or the target vehicle torque distribution corresponds to a vehicle speed at which the vehicle 10 achieves optimal energy consumption efficiency relative to a portion of a route traversed by the vehicle 10.

[0060] In some embodiments, the system 100 may include a vehicle propulsion controller (VPC) 102, a human-machine interface (HMI) control 104, a vehicle sensor 108, a torque controller 110, a brake controller 112, a torque distribution controller 116, a brake system 118, a propulsion system 120, and a display 122. In some embodiments, the display 122 may include a portion of a dashboard or console of the vehicle 10, a navigation display of the vehicle 10, or other suitable displays of the vehicle 10. In some embodiments, the display 122 may be provided on a computing device such as a mobile computing device used by a driver. In some embodiments, the system 100 may include a propulsion adjustment controller (PAC) 124, a global positioning system (GPS) antenna 126 communicating with a mapping feature module (not shown), an advanced driver assistance system (ADAS) module 128, and a vehicle to other systems (V2X) communication module 130. The V2X communication module 130 may be configured to communicate with other vehicles, other infrastructure (e.g., such as, for example, transportation infrastructure, mobile computing devices, and / or other suitable infrastructure), remote computing devices (e.g., remote computing devices 132), other suitable systems, or combinations thereof. As will be described, the system 100 may communicate with one or more remote computing devices 132. In some embodiments, at least some of the components of the system 100 may be disposed in a propulsion control module (PCM) or other onboard vehicle computing devices. For example, at least the PAC 124 and the VPC 102 may be disposed in the PCM. In some embodiments, the system 100 may be at least partially disposed in the PCM, while other components of the system 100 may be disposed on a stand-alone computing device having a memory storing instructions that, when executed by a processor, cause the processor to perform operations of the components. For example, the PAC 124 may be disposed on a memory and executed by a processor. It should be understood that, as will be described, the system 100 may include any combination of computing devices disposed locally in the vehicle 10 and / or computing devices disposed remotely.

[0061] In some embodiments, VPC 102 may include an autonomous vehicle propulsion system. For example, VPC 102 may include a cruise control mechanism, an adaptive cruise control mechanism, an automatic braking system, other suitable autonomous vehicle propulsion systems, or a combination thereof. Additionally or alternatively, VPC 102 may include or may be a portion of an autonomous vehicle system that controls all or a portion of vehicle propulsion, steering, braking, safety, route management, other autonomous features, or a combination thereof. It should be understood that although only limited components of system 100 are shown, system 100 may include additional autonomous components or other suitable components.

[0062] The VPC 102 communicates with one or more human-machine interfaces (HMIs) 104. The HMI controls 104 may include any suitable HMI. For example, the HMI controls 104 may include a plurality of switches disposed on a steering wheel of the vehicle 10, disposed on a dashboard or console of the vehicle 10, or disposed at any other suitable location on the vehicle 10. In some embodiments, the HMI controls 104 may be disposed on a mobile computing device, such as a smart phone, a tablet, a laptop computer, or other suitable mobile computing device. In some embodiments, the driver of the vehicle 10 may interact with the HMI controls 104 to use the VPC 102 to control vehicle propulsion and / or other features of the VPC 102. For example, the driver may actuate an HMI switch of an HMI control 104 disposed on a steering wheel of the vehicle 10. The HMI controls 104 may transmit a signal to the VPC 102. The signal may indicate a desired vehicle speed selected by the driver. The VPC 102 generates a torque demand corresponding to a desired vehicle speed and transmits the torque demand to the torque controller 110. The torque controller 110 communicates with the propulsion system 120 and / or other vehicle propulsion systems of the vehicle 10. The torque controller 110 uses the torque demand to selectively control the propulsion system 120 and / or other vehicle propulsion systems to achieve the desired vehicle speed. The driver can increase or decrease the desired vehicle speed by actuating an additional switch of the HMI control 104. The VPC 102 can adjust the torque demand to achieve an increase or decrease in the desired vehicle speed.

[0063] The VPC 102 may continuously adjust the torque demand in order to maintain the desired vehicle speed. For example, the VPC 102 may communicate with the vehicle sensor 108. The vehicle sensor 108 may include a camera, a speed sensor, a proximity sensor, other suitable sensors as will be described, or a combination thereof. The VPC 102 may receive a signal from the vehicle sensor 108 indicating the current vehicle speed. When the signal indicates that the current vehicle speed is different from the desired vehicle speed, the VPC 102 may adjust the torque demand to adjust the vehicle speed. For example, the vehicle 10 may traverse a slope that causes the vehicle 10 to reduce the current vehicle speed (e.g., because the torque demand applied by the torque controller 110 is insufficient to maintain the vehicle speed while on the slope). The VPC 102 may increase the torque demand in order to adjust the current vehicle speed to achieve the desired vehicle speed.

[0064] In some embodiments, such as when the VPC 102 includes an adaptive cruise control mechanism, the VPC 102 can adjust the torque demand based on the proximity of the leading vehicle (e.g., the vehicle immediately in front of the vehicle 10). For example, the VPC 102 can receive information indicating the presence of the leading vehicle from the vehicle sensor 108. The information can be captured by the vehicle sensor 108 using a camera, a proximity sensor, a radar, a V2X communication module 130, other suitable sensors or input devices, or a combination thereof. The VPC 102 can determine whether to maintain the desired vehicle speed or increase or decrease the torque demand to increase or decrease the current vehicle speed. For example, the driver can use the HMI control 104 to indicate to maintain the pace of the leading vehicle while maintaining a safe stopping distance between the vehicle 10 and the leading vehicle. If the leading vehicle is traveling faster than the vehicle 10, the VPC 102 can selectively increase the torque demand, and if the leading vehicle is traveling slower than the vehicle 10, the VPC 102 can selectively reduce the torque demand.

[0065] When the leading vehicle comes to a complete stop, the VPC 102 may bring the vehicle 10 to a complete stop. For example, the VPC 102 may communicate with the brake controller 112 to send a plurality of signals over a period of time that instruct the brake controller 112 to control vehicle braking (e.g., the VPC 102 may bring the vehicle 10 to a complete stop over a period of time to avoid a sudden stop of the vehicle, however, in the event that the leading vehicle suddenly stops, the VPC 102 brings the vehicle 10 to a sudden stop to avoid a collision with the leading vehicle). The brake controller 112 may communicate with the brake system 118. The brake system 118 may include a plurality of brake components that are actuated in response to the brake controller 112 implementing a braking procedure based on a plurality of signals from the VPC 102. In some embodiments, the VPC 102 may implement engine braking through a regenerative braking system by adjusting the torque demand to allow the vehicle 10 to come to a stop without using the brake system 118, or the VPC 102 may use a combination of regenerative braking and the brake system 118 to bring the vehicle 10 to a complete stop. To resume vehicle propulsion control, the driver instructs the use of HMI controls 104 to resume vehicle propulsion control (e.g., VPC 102 is not configured to resume vehicle propulsion control without interaction from the driver). In some embodiments, vehicle 10 may include a higher level of automation including a higher level of propulsion control, as described, and vehicle 10 may include appropriate controls for bringing vehicle 10 to a complete stop without interaction with the driver of vehicle 10.

[0066] In some embodiments, the VPC 102 can determine a torque distribution in order to utilize the internal combustion engine and the electric motor of the vehicle 10 (e.g., where the vehicle 10 is a hybrid vehicle). It should be understood that although only an internal combustion engine and an electric motor are described, the vehicle 10 may include any hybrid combination of any suitable vehicle engine and electric motor. The torque distribution indicates the portion of the torque demand to be applied to the internal combustion engine and the portion of the torque demand to be applied to the electric motor. For example, when the torque demand is below a threshold, the electric motor can be used for vehicle propulsion. However, when the torque demand is above a threshold (e.g., such as when the vehicle 10 is on a steep slope), the internal combustion engine can provide at least a portion of the vehicle propulsion to assist the electric motor. The VPC 102 transmits the torque distribution to the torque distribution controller 116. The torque distribution controller 116 communicates with the propulsion system 120 to apply the torque distribution.

[0067] In some embodiments, the VPC 102 includes a plurality of safety controls. For example, the VPC 102 may determine whether to increase or decrease the torque demand based on input from the safety control, thereby increasing or decreasing the desired vehicle speed or the current vehicle speed. The safety control may receive input from the vehicle sensor 108. For example, the safety control may receive proximity sensor information, camera information, other information, or a combination thereof, and may generate a safety signal to the VPC 102 indicating that one or more safety operations are to be performed. For example, in the case where the vehicle ahead comes to a sudden stop, the safety control may generate a safety signal to the VPC 102 indicating that the vehicle 10 is to be brought to a complete stop immediately based on the proximity information from the vehicle sensor 108. In some embodiments, the VPC 102 may determine whether to apply the desired vehicle speed set by the driver using the HMI control 104 based on the signal from the safety control. For example, the driver may increase the desired vehicle speed, which may cause the vehicle 10 to be closer to the vehicle ahead (e.g., if the desired vehicle speed is achieved, the vehicle 10 will travel faster than the vehicle ahead). The VPC 102 may determine that the desired vehicle speed does not apply, and instead may provide an indication to the display 122 indicating to the driver that it may be unsafe to increase the desired vehicle speed, or the VPC 102 may ignore the increase in the desired vehicle speed. In some embodiments, the VPC 102 may communicate with a transmission controller module (TCM). The VPC 102 may receive information from the TCM (e.g., the gear automatically selected), and may determine and / or adjust the total torque request based on the information received from the TCM.

[0068] As described, the system 100 includes a PAC 124. The PAC 124 is configured to determine a target vehicle speed profile based on at least route information for a route being traversed by the vehicle 10, vehicle parameters of the vehicle 10, information about other vehicles in proximity to the vehicle 10, traffic information, weather information, current vehicle speed, desired vehicle speed, other information, or a combination thereof. As will be described, the PAC 124 may determine the target vehicle speed profile based on an energy consumption profile of the vehicle 10. The energy consumption profile may be generated using the information described above and may indicate optimal energy consumption for the vehicle 10 for various route characteristics, such as road grade, curvature, traffic, speed limits, stop signs, traffic signals, other route characteristics, or a combination thereof.

[0069] The PAC 124 receives route characteristics (e.g., road slope characteristics, route distance, and route direction), vehicle parameters, traffic characteristics, weather characteristics, vehicle-to-vehicle parameters, other information or characteristics, or a combination thereof. In some embodiments, the PAC 124 receives at least some of the route characteristics from a mapping characteristics module based on location information from a GPS antenna 126. The mapping characteristics module is disposed within the vehicle 10 (e.g., disposed within the system 100), or may be disposed on a remote computing device such as a remote computing device 132. When the mapping characteristics module is disposed on the remote computing device 132, the GPS antenna 126 may capture various global positioning signals from various global positioning satellites or other mechanisms. The GPS antenna 126 may transmit the captured signals to the mapping characteristics module. The mapping characteristics module may generate route characteristics based on the signals received from the GPS antenna 126 and transmit the route characteristics to the PAC 124. For example, the PAC 124 may receive route distance, route direction, road slope information for the route, other route characteristics, most likely path (MPP) information, or a combination thereof. In some embodiments, the PAC 124 may receive traffic signal location information, traffic stop sign location information, posted speed limit information, lane change information, other route characteristics or information, or combinations thereof from a mapping characteristics module based on location information from the GPS antenna 126 .

[0070] The PAC 124 may receive further vehicle parameters from the vehicle sensors 108. For example, the vehicle sensors 108 may include an energy level sensor (e.g., a fuel level sensor or a battery charge sensor), a fuel sensor, a speed sensor, a weight sensor, other suitable sensors, or combinations thereof. The PAC 124 may receive from the vehicle sensors 108 the energy level of the vehicle 10, the current weight of the vehicle 10, the fuel condition of the vehicle 10, tire inflation information of the vehicle 10, the current vehicle speed, engine temperature information, other suitable vehicle parameters of the vehicle 10, or combinations thereof. In some embodiments, the vehicle sensors 108 may include weather sensors, such as precipitation sensors or humidity sensors, air pressure sensors, ambient temperature sensors, other suitable sensors, or combinations thereof. The PAC 124 may receive from the vehicle sensors 108 current weather information, such as precipitation information, air pressure information, ambient temperature information, other suitable weather information, or combinations thereof.

[0071] The PAC 124 may receive at least some of the route characteristics from the ADAS module 128. The ADAS module 128 may help the driver of the vehicle 10 improve vehicle safety and road safety. The ADAS module 128 may be configured to automate and / or adapt and enhance the vehicle system for safety and better driving. The ADAS module 128 may be configured to warn the driver of the vehicle 10 of upcoming traffic conditions or disabled vehicles, and / or be configured to warn the vehicle 10 of vehicles approaching the vehicle 10 in order to avoid collisions and accidents. Further, the ADAS module 128 may autonomously avoid collisions by implementing safety measures and taking over control of the vehicle 10, such as, by automatic lighting, initiating adaptive cruise control (e.g., via the VPC 102) and collision avoidance (e.g., by using the VPC 102 or directly using the brake controller 112 to control the trajectory of the vehicle 10 or to stop the vehicle 10 completely). The PAC 124 may receive information from the ADAS module 128 , such as traffic characteristics, vehicle proximity information, disabled vehicle information, other suitable information, or combinations thereof.

[0072] The PAC 124 may receive at least some of the route characteristics from the V2X communication module 130. The V2X communication module 130 is configured to communicate with other systems near or away from the vehicle 10, as described above, to obtain and share information, such as traffic information, vehicle speed information, construction information, other information, or a combination thereof. The PAC 124 may receive other vehicle speed information, other vehicle position information, other traffic information, construction information, other suitable information, or a combination thereof from the V2X communication module 130.

[0073] The PAC 124 may receive at least some of the route characteristics from the remote computing device 132. For example, the PAC 124 may receive from the remote computing device 132 further information related to route distance, route direction, road grade information for the route, traffic information, construction information, other vehicle location information, other vehicle speed information, vehicle maintenance information for the vehicle 10, other route characteristics, or a combination thereof. Additionally or alternatively, the PAC 124 may receive from the remote computing device 132 vehicle parameters such as the make and model of the vehicle 10, the energy efficiency of the vehicle 10 provided by the manufacturer, the weight of the vehicle 10, other vehicle parameters, or a combination thereof. In some embodiments, the PAC 124 may receive from the remote computing device 132 traffic signal location information, traffic stop sign location information, posted speed limit information, lane change information, other route characteristics or information, or a combination thereof. The remote computing device 132 may include any one or more suitable computing devices, such as a cloud computing device or system, one or more remotely located servers, a remotely located or nearby located mobile computing device or application server that provides information to the mobile computing device, other suitable remote computing devices, or combinations thereof. The remote computing device 132 is located remotely from the vehicle 10, such as in a data center or other suitable location. In some embodiments, the remote computing device 132 may be located within the vehicle 10 (e.g., a mobile computing device used by a driver of the vehicle 10).

[0074] In some embodiments, the PAC 124 may receive traffic signal information, such as traffic signal phase and timing (SPaT) from an intelligent algorithm used by a traffic data provider. The SPaT information may indicate when a traffic signal is changing and / or indicate the timing of a traffic signal.

[0075] The PAC 124 may receive route characteristics and / or vehicle parameters from the driver of the vehicle 10. For example, the driver may interact with an interface of the PAC 124, such as using the display 122 or using a mobile computing device, to provide vehicle parameters of the vehicle 10, such as vehicle weight, vehicle make and model, vehicle age, vehicle maintenance information, vehicle identification number, number of passengers, load information (e.g., luggage volume or other load information), other vehicle parameters, or a combination thereof. Additionally or alternatively, the driver may provide route characteristics such as a route map, route distance, other route characteristics, or a combination thereof to the PAC 124. In some embodiments, the PAC 124 learns the behavior of the driver of the vehicle 10. For example, the PAC 124 monitors the driver's vehicle speed relative to the posted speed limit or whether the driver implements the vehicle speed recommendation provided by the PAC 124 as will be described.

[0076] In some embodiments, the PAC 124 can learn traffic patterns for known routes traversed by the vehicle 10. For example, the PAC 124 can track traffic conditions as the vehicle 10 routinely or periodically traverses one or more routes. The PAC 124 can determine the traffic patterns for these routes based on the monitored traffic conditions. In some embodiments, the PAC 124 receives the traffic patterns for the routes that the vehicle 10 is traversing from the remote computing device 132 or from a mapping feature module based on signals from the GPS antenna 126, as described.

[0077] It should be understood that the PAC 124 may receive any characteristics or information associated with routes, traffic, signs and signals, other vehicles, vehicle parameters of the vehicle 10, any other suitable characteristics or information, including those described or not described herein, from any of the components described or not described herein. Additionally or alternatively, the PAC 124 may be configured to learn any suitable characteristics or information described or not described herein.

[0078] In some embodiments, the PAC 124 is configured to control the propulsion of the vehicle 10. The PAC 124 may be an integrated component of the VPC 102, or may be an overlay component that communicates or interacts with the VPC 102 and / or other components of the vehicle 10. Additionally or alternatively, the PAC 124 may be provided on a mobile computing device (such as a smart phone that uses at least some of the information described above) to present a recommended vehicle speed to the driver of the vehicle 10. In some embodiments, the VPC 102 may include an adaptive cruise control mechanism. As described, the adaptive cruise control mechanism is configured to maintain the desired vehicle speed provided by the driver of the vehicle 10 using the HMI control 104, and the adaptive cruise control mechanism is configured to maintain a safe distance between the vehicle 10 and the vehicle ahead. In addition, the adaptive cruise control mechanism is configured to stop the vehicle 10 completely in response to the vehicle ahead stopping completely. As described, the adaptive cruise control mechanism cannot restart the vehicle propulsion without interaction from the driver of the vehicle 10. Additionally, the adaptive cruise control mechanism is unable to bring the vehicle 10 to a complete stop without a leading vehicle. Therefore, the VPC 102 (e.g., the adaptive cruise control mechanism) is unable to utilize energy-efficient vehicle propulsion control (e.g., such as coasting to a stop in response to determining that the vehicle 10 is approaching a stop sign). The PAC 124 is configured to determine a target vehicle propulsion profile based on an energy consumption profile of the vehicle 10, the target vehicle propulsion profile may include one or more target vehicle speeds and one or more target vehicle speeds and one or more target torque distributions. The PAC 124 may determine a target torque demand based on the profile of the target vehicle speed and / or the target torque distribution.

[0079] In some embodiments, the PAC 124 uses the information described above to determine a vehicle energy consumption profile. For example, the PAC 124 may determine a vehicle consumption profile using the following: vehicle weight, vehicle energy efficiency provided by the manufacturer, historical data corresponding to the vehicle 10 or a similar vehicle indicating the energy consumption of the vehicle 10 or a similar vehicle when traversing portions of a particular route or a particular road grade, or other suitable route or road information, other suitable vehicle parameters, or a combination thereof. The vehicle energy consumption profile may indicate that the vehicle 10 consumes a specified amount of energy (e.g., a specified amount of energy within a tolerance mileage) when operating at a specific vehicle speed (a specific vehicle speed within tolerance) while traversing a route with specific roads, traffic, and other conditions. For example, the energy consumption of the vehicle 10 may be greater when the vehicle 10 is on a slope, and the energy consumption of the vehicle 10 may be less when the vehicle 10 is coasting to a stop. In some embodiments, the PAC 124 receives or retrieves (such as through the remote computing device 132 ) a vehicle energy profile for the vehicle 10 that is determined remotely from the vehicle 10 .

[0080] The PAC 124 is configured to determine a profile of a target vehicle speed and / or target torque distribution for a portion of the route being traversed by the vehicle 10 using a vehicle energy consumption profile and various route characteristics (e.g., including route characteristics of the selected route and / or route characteristics associated with the MPP). For example, the PAC 124 may determine that the vehicle 10 is approaching a particular grade change on a portion of the route being traversed by the vehicle 10. The PAC 124 uses the vehicle energy consumption profile to identify a vehicle speed (within a threshold mileage of a desired vehicle speed provided by the driver to the VPC 102) and / or torque distribution with optimal energy consumption for the grade change for the portion of the route being traversed by the vehicle. In some embodiments, the PAC 124 may determine the vehicle speed and torque distribution using historical energy consumption for a known route, such as a route previously traversed by the vehicle 10 or a similar vehicle. The PAC 124 determines a target torque demand based on the identified vehicle speed, and determines a target torque distribution based on the identified torque distribution. It should be understood that, as described, the PAC 124 continuously monitors the various characteristics received and continues to generate a profile of vehicle speed and / or target torque distribution so that the vehicle 10 maintains optimal or improved energy consumption while maintaining driver and / or passenger comfort (e.g., by avoiding sudden, unnecessary changes in vehicle speed).

[0081] In some embodiments, the PAC 124 may be configured to determine when the vehicle 10 should glide to achieve optimal or improved energy consumption of the vehicle 10. For example, the PAC 124 may use known traffic conditions, as described, to determine when the vehicle 10 should glide. Additionally or alternatively, the PAC 124 may learn known traffic conditions, as described, and may determine, for example, based on the time of day, whether the vehicle 10 should glide in an area along a route known to typically have traffic. In some embodiments, the PAC 124 may use SPaT information to determine when the vehicle 10 should glide in response to a change in a traffic signal. Additionally or alternatively, the PAC 124 may determine to increase a target vehicle speed associated with a target vehicle speed profile (e.g., within a posted speed limit) to increase the likelihood that the vehicle 10 arrives at a traffic signal when the traffic signal indicates forward based on traffic single timing, which may allow the vehicle 10 to avoid having to stop at a traffic signal.

[0082] In some embodiments, the PAC 124 may be configured to calculate a glide function and / or a road load function (see equation (2)) to identify specific vehicle parameters using speed-dependent drag. The parameters of the road load function include vehicle parameters that may be received by the PAC 124 as described, such as vehicle mass or weight, vehicle rolling friction, vehicle drag coefficient, other vehicle parameters, or combinations thereof. These parameters may then be updated using a glide self-learning function, such that the PAC 124 identifies or requests a glide sequence (e.g., from historical information and / or from a remote computing device 132), and calculates a glide function result. The PAC 124 may calculate a glide function when requested by the driver of the vehicle 10, who may be prompted by the PAC 124 to perform a specific learning maneuver, or may learn in the background. Equation (2) Speed-related drag: F = wind, tire, bearing and other forces plus inertial forces associated with acceleration plus gravity associated with slope: F=(A+(B*v)+(C*v 2 ))+((1+driven axle %+non-driven axle %)*(test mass*acceleration))+(test mass*g*sin(arc tan(slope %)))

[0083] Among them, A represents the resistance that is constant and does not vary with speed (e.g., bearings, seals, tires, etc.), B represents the resistance that varies linearly with speed (e.g., transmission, differential, etc.), and C represents the resistance that varies with the square of the speed (e.g., wind force, tire deformation, etc.).

[0084] As described, the PAC 124 may control or interact with the VPC 102, and / or interact with the driver of the vehicle 10, to achieve a target vehicle speed and / or a target torque distribution profile, which may result in optimal or improved energy consumption efficiency of the vehicle 10. Additionally or alternatively, the PAC 124 may control or interact with the VPC 102 to bring the vehicle 10 to a complete stop in response to the vehicle 10 approaching a stop sign, a traffic signal, traffic, a disabled vehicle, or other suitable condition. The PAC 124 may also control or interact with the VPC 102 to resume vehicle propulsion after the vehicle 10 has come to a complete stop.

[0085] In some embodiments, the PAC 124 may control or interact with the VPC 102 using virtual inputs to achieve a target vehicle speed and / or a target torque distribution profile. As described, the VPC 102 may receive a desired vehicle speed from a driver of the vehicle 10 using the HMI controls 104. Additionally or alternatively, the VPC 102 (e.g., when the VPC 102 includes an adaptive cruise control mechanism) may adjust the desired vehicle speed in response to the speed of the vehicle ahead.

[0086] In some embodiments, when the driver of the vehicle 10 first engages the VPC 102 during a critical period, the PAC 124 initializes the VPC 102 using the desired speed provided by the driver of the vehicle 10. The PAC 124 can then provide virtual inputs to the VPC 102 to control the vehicle speed to achieve optimal or improved energy efficiency of the vehicle 10. In some embodiments, the PAC 124 can generate virtual inputs including virtual HMI signals that, when received by the VPC 102, can cause the VPC 102 to be enabled, disabled, and / or set or adjust the current vehicle speed. The PAC 124 generates the virtual HMI signals based on the target vehicle speed profile. The PAC 124 communicates and / or interacts with the HMI controls 104. The PAC 124 replaces the HMI signals provided by the driver of the vehicle 10 with the virtual HMI signals generated by the PAC 124. As described, the VPC 102 includes a plurality of safety controls. As described, the VPC 102 then applies the target vehicle speed indicated by the virtual HMI signal associated with the target vehicle speed profile in the same manner that the VPC 102 applies the desired vehicle speed provided by the driver using the HMI control 104. The VPC 102 may determine whether to apply the target vehicle speed and / or target torque split indicated by the virtual HMI signal based on safety controls.

[0087] In some embodiments, the PAC 124 generates virtual inputs including a virtual car ahead in order to control the VPC 102 to bring the vehicle 10 to a complete stop in the absence of an actual car ahead. For example, as described, the PAC 124 can stop the vehicle 10 when the vehicle 10 approaches a stop sign, a traffic signal, traffic, a disabled vehicle, or other suitable stopping conditions that the vehicle 10 may encounter. The PAC 124 replaces information received by the VPC 102 from the vehicle sensors 108 (e.g., information that the VPC 102 uses to detect an actual car ahead) with virtual information, signals, and / or inputs corresponding to the virtual car ahead.

[0088] The VPC 102 detects the presence of the virtual front car and performs operations associated with following the front car (e.g., maintaining a safe distance between the vehicle 10 and the front car, keeping pace with the front car, and stopping the vehicle in response to the front car being within the target range of the vehicle 10 and about to come to a complete stop). The PAC 124 can then control the virtual speed of the virtual front car based on the target vehicle speed profile. The VPC 102 can then adjust the current vehicle speed of the vehicle 10 to follow the virtual front car. In this way, the PAC 124 can implement the target vehicle speed profile of the vehicle 10 to provide optimal or improved energy efficiency of the vehicle 10. While the PAC 124 is controlling the VPC 102 using the described virtual inputs, the vehicle sensors 108 (such as cameras, radars, proximity sensors, etc.) continue to provide information to the VPC 102 so that the VPC 102 can continue to detect actual vehicles or objects in front of the vehicle 10 as the VPC 102 applies or follows the virtual inputs provided by the PAC 124. The safety controls of the VPC 102 are configured to override the VPC 102 (including the virtual inputs provided by the PAC 124) to safely bring the vehicle 10 to a complete stop or to increase or decrease vehicle speed in response to information from the vehicle sensors 108.

[0089] In some embodiments, the PAC 124 can communicate directly with the VPC 102 and the torque distribution controller 116 to provide a recommended target torque demand and a target torque distribution to the VPC 102 and the torque distribution controller 116, respectively, to achieve optimal or improved energy efficiency for the vehicle 10. For example, the VPC 102 can be configured to receive an HMI signal (e.g., as described), follow a leading vehicle based on information from the vehicle sensors 108 (e.g., as described), and receive a recommended target vehicle speed signal from the PAC 124. The VPC 102 can determine whether to apply the target vehicle speed indicated by the recommended target vehicle speed signal, for example, based on driver input, detection of a leading vehicle, and / or safety control of the VPC 102.

[0090] The torque split controller 116 may be configured to receive a recommended torque split signal from the VPC 102 based on driver input as described, and may be configured to receive a recommended target torque split signal from the PAC 124. It should be appreciated that the PAC 124 may transmit the recommended target torque split signal to the VPC 102, which may then transmit the recommended target torque split signal and / or a recommended torque request signal (e.g., generated by the VPC 102) to the torque split controller 116. The torque split controller 116 determines whether to apply the target torque split indicated by the recommended target torque split signal based on a comparison with the torque split indicated by the recommended torque split signal provided by the VPC 102 and / or based on the existing propulsion state of the vehicle 10 (e.g., including diagnostic conditions).

[0091] In some embodiments, the PAC 124 may communicate with the display 122 to provide an indicator to the driver that the vehicle speed is changing to improve the energy efficiency of the vehicle 10. For example, the PAC 124 may use the display 122 to illustrate an energy efficiency symbol that indicates to the driver of the vehicle 10 that the vehicle speed is changing to improve the energy efficiency of the vehicle 10.

[0092] In some embodiments, as described above, the VPC 102 may not include an adaptive cruise control system, and may include a basic cruise control system. Additionally or alternatively, the driver of the vehicle 10 may not occupy the VPC 102 in order to control the propulsion of the vehicle 10 (e.g., the driver of the vehicle 10 may manually control the propulsion). Accordingly, the PAC 124 is configured to provide a recommendation to the driver indicating a target vehicle speed profile for the target vehicle speed profile. The recommendation may be provided to the driver of the vehicle 10 using one or more integrated displays of the vehicle 10, such as a display 122 that may include a portion of the dashboard or console of the vehicle 10, a navigation display of the vehicle 10, or other suitable integrated displays of the vehicle 10. In some embodiments, a mobile computing device within the vehicle 10 may be used to provide the driver of the vehicle 10 with a recommendation. The recommendation may include a symbol or text message indicating to the driver of the vehicle 10 to increase or decrease the vehicle speed. Additionally or alternatively, the recommendation may include a coasting recommendation that is displayed for a calibrated amount of time and then withdrawn in response to the driver of the vehicle 10 ignoring the recommendation. The recommendation may include information indicating that the recommendation is in response to a change in speed limit, a stop sign that the vehicle 10 is approaching, traffic signal timing, and status, or other information. The information may be displayed visually and may decay as the vehicle 10 recommendation becomes outdated.

[0093] The driver of the vehicle 10 can determine to honor the recommendation and change the vehicle speed accordingly, or the driver can choose to ignore the recommendation. The PAC 124 can be configured to monitor driving action in response to the recommendation to determine whether the driver of the vehicle 10 honors the recommendation or ignores the recommendation. The PAC 124 can determine whether to adjust the recommendation based on the monitored driver action. For example, the PAC 124 can determine not to recommend gliding in response to the driver ignoring the gliding recommendation of a threshold number. Additionally or alternatively, the PAC 124 can use the monitored driver action and the route traversed by the vehicle 10 to determine whether the driver of the vehicle 10 honors the recommendation at certain parts of the route and ignores the recommendation at other parts of the route. The PAC 124 can selectively provide recommendations to the driver of the vehicle 10 based on the monitored driver action and the vehicle route. Additionally or alternatively, the PAC 124 can monitor driver action in response to recommendations based on traffic patterns, stop signs, traffic signals, etc. The PAC 124 may selectively determine whether to provide a recommendation to the driver of the vehicle 10 based on driver actions monitored in response to traffic patterns, stop signs, traffic signals, and the like.

[0094] In some embodiments, the PAC 124 may be configured to estimate the remaining range of a vehicle battery of the vehicle 10. For example, the PAC 124 may identify at least one route characteristic of a portion of the selected route, as described. The PAC 124 may determine a vehicle energy consumption profile for the vehicle 10 based at least on historical data indicating vehicle energy consumption of at least a portion of a route previously traversed by the vehicle, the at least a portion of the route having at least one route characteristic corresponding to at least one route characteristic of the portion of the selected route.

[0095] In some embodiments, the PAC 124 may not receive the selected route. For example, the operator of the vehicle 10 may use the vehicle 10 to traverse any route without utilizing route selection. The map feature module or other suitable navigation system of the vehicle 10 may provide the PAC 124 with an MPP starting from the current location of the vehicle 10. The MPP may include at least one route segment that the vehicle 10 is most likely to traverse. The map feature module or other suitable navigation system may determine at least one route segment that the vehicle 10 is most likely to traverse based on historical information of the vehicle 10 (e.g., including but not limited to any historical information of the vehicle 10 described herein), historical information of one or more other vehicles (e.g., including but not limited to any historical information of any vehicle described herein), and / or any other suitable information.

[0096] For example, the PAC 124 may receive MPP information for a desired route to be followed within a relatively short distance (e.g., between the current location of the vehicle 10 and an upcoming intersection or other suitable location). The MPP information may correspond to the predicted destination of the vehicle 10 and the operator's best possible route to that destination. The map feature module or other suitable navigation system may determine the MPP information based solely on the past behavior of other operators (e.g., most operators at the current location of the vehicle 10 and traveling in its current direction follow a particular onward route), personal information of the current operator of the vehicle 10 that has been collected and analyzed (e.g., the operator will travel to a certain location, a series of locations at a specific date and time, etc.), and / or any other suitable information associated with the vehicle 10, other vehicles, the operator of the vehicle 10, and / or other operators of other vehicles.

[0097] PAC 124 may identify at least one route characteristic of at least a portion of the route segment associated with the MPP. PAC 124 may determine a vehicle energy consumption profile for vehicle 10 based at least on historical data indicating vehicle energy consumption of at least a portion of a route previously traversed by vehicle 10, at least a portion of the route having at least one route characteristic that corresponds to at least one route characteristic of a portion of the route segment associated with the MPP.

[0098] The PAC 124 may determine the current SoC of a vehicle battery of the vehicle 10. For example, the PAC 124 may receive data from one or more of the sensors of the vehicle 10, including but not limited to a battery sensor configured to determine the SoC of the vehicle battery. It should be understood that while a single vehicle battery is described herein, the vehicle 10 may include any suitable number of batteries, and the PAC 124 may use the SoC of each battery to estimate the remaining range of the vehicle 10. In addition to or as an alternative to the state of charge of the battery, the PAC 124 may use the energy state of the battery.

[0099] For example, the PAC 124 may determine a route energy consumption profile for the selected route or MPP based on at least one route characteristic of a portion of the selected route or MPP and the vehicle energy consumption profile (e.g., the route energy consumption profile may represent predicted energy usage for the route). The PAC 124 may calculate an estimated remaining charge of the vehicle battery at the end of the selected route or MPP based on the charge state of the vehicle battery and the route energy consumption profile. In addition to or as an alternative to the remaining charge of the battery, the PAC 124 may determine a remaining energy range of the vehicle.

[0100] The PAC 124 can determine whether the estimated remaining charge of the vehicle battery is within the vehicle battery range (e.g., the vehicle battery range can represent an acceptable range for continuing along the route). The vehicle battery range can include an upper limit and a lower limit. The vehicle battery range can be set by the driver (e.g., as one of the driver settings) or programmatically during vehicle component manufacturing. The vehicle battery range can include a range of values, where the lower limit is set to the number of miles of the selected route or MPP, and the upper limit is set to a predetermined number of miles greater than the lower limit. It should be understood that the vehicle battery range includes any suitable mileage. The PAC 124 can generate a first indication in response to determining that the estimated remaining charge is within the vehicle battery range. The first indication can include an estimated remaining charge of the vehicle battery at the end of the selected route or MPP.

[0101] The PAC 124 may generate a second indication in response to determining that the estimated remaining charge is less than the lower limit of the vehicle battery charge range. The second indication may include a warning indicating that the vehicle battery may be exhausted before the vehicle 10 reaches the end of the selected route or MPP. The PAC 124 provides one of the first indication and the second indication (e.g., based on the determination result of whether the remaining charge of the vehicle battery is within the vehicle battery charge range). For example, the PAC 124 may provide the first indication and / or the second indication at a display (such as the display 122 of the vehicle 10), at a mobile computing device, to an autonomous controller of the vehicle 10, and / or the like.

[0102] In some embodiments, the PAC 124 may determine a target vehicle speed profile based on at least one route characteristic, a vehicle energy consumption profile, and a state of charge of a vehicle battery in response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range. The PAC 124 may generate a second indication. The second indication may further include a recommendation to follow the target vehicle speed profile to avoid exhausting the vehicle battery before the vehicle 10 reaches the end of the selected route or MPP. The PAC 124 may control propulsion of the vehicle 10 based on the target vehicle speed profile and / or by providing a recommendation to the operator of the vehicle to achieve the target vehicle speed profile, as described herein.

[0103] In some embodiments, the PAC 124 and / or VPC 102 may perform the methods described herein. However, the methods described herein as being performed by the PAC 124 and / or VPC 102 are not meant to be limiting, and any type of software executed on a controller may perform the methods described herein without departing from the scope of the present disclosure. For example, a controller, such as a processor executing software within a computing device on the vehicle 10, may perform the methods described herein.

[0104] Figure 5 is a flow chart generally illustrating a vehicle propulsion control method 300 according to the principles of the present disclosure. At 302, the method 300 receives vehicle parameters. For example, the PAC 124 may receive various vehicle parameters of the vehicle 10 from any of the components described herein.

[0105] At 304, the method 300 determines a vehicle energy consumption profile. For example, the PAC 124 determines an energy consumption profile for the vehicle 10 using vehicle parameters and / or other route characteristics, such as historical route characteristics associated with routes previously traversed by the vehicle, route characteristics associated with routes previously traversed by similar vehicles (e.g., from the remote computing device 132 and / or the V2X communication module 130), other suitable route characteristics, or a combination thereof.

[0106] At 306, the method 300 receives route characteristics. For example, the PAC 124 receives various route characteristics (e.g., route characteristics of the route that the vehicle 10 is currently traversing or will traverse) and other information from any other components described herein. In some embodiments, the method continues at 308. In some embodiments, the method continues at 310.

[0107] At 308, the method 300 determines a profile for a target vehicle speed and / or target torque distribution. For example, the PAC 124 determines the profile for the target vehicle speed and / or target torque distribution based on vehicle parameters as described, route characteristics, an energy consumption profile of the vehicle 10, other received information received from various components described herein. The profile for the target vehicle speed and / or target vehicle torque distribution corresponds to a vehicle speed and / or torque distribution that provides optimal or improved energy consumption efficiency of the vehicle 10 when implemented by the vehicle 10.

[0108] At 310, the method 300 generates at least one virtual input. For example, the PAC 124 generates at least one virtual input. The virtual input may include a virtual HMI signal and / or a virtual front vehicle. When applied by the VPC 102, the virtual input achieves a target vehicle speed and / or a target torque distribution.

[0109] At 312, the method 300 provides a virtual input to the vehicle propulsion controller. For example, the PAC 124 may replace an HMI signal transmitted from the HMI control 104 based on input from the driver of the vehicle 10 with a virtual HMI signal. Additionally or alternatively, the PAC 124 may replace the vehicle sensor information provided by the vehicle sensor 108 to indicate a virtual leading vehicle to the VPC 102. For example, the VPC 102 may apply the virtual HMI signal and / or may follow the virtual leading vehicle in order to achieve a target vehicle speed and / or torque distribution. For example, the PAC 124 may continuously update the target vehicle speed and / or target torque distribution as the vehicle 10 continues to traverse the route and based on updated traffic information, vehicle information, route information, other information, or a combination thereof.

[0110] Figure 6 4 is a flow chart generally illustrating an alternative vehicle propulsion control method 400 according to the principles of the present disclosure. At 402, the method 400 receives vehicle parameters. For example, the PAC 124 may receive various vehicle parameters of the vehicle 10 from any of the components described herein.

[0111] At 404, the method 400 determines a vehicle energy consumption profile. For example, the PAC 124 determines an energy consumption profile for the vehicle 10 using vehicle parameters and / or other route characteristics, such as historical route characteristics associated with routes previously traversed by the vehicle, route characteristics associated with routes previously traversed by similar vehicles (e.g., from the remote computing device 132 and / or the V2X communication module 130), other suitable route characteristics, or a combination thereof.

[0112] At 406, the method 400 receives route characteristics. For example, the PAC 124 receives various route characteristics (e.g., route characteristics of the route that the vehicle 10 is currently traversing or will traverse) and other information from any other components described herein. In some embodiments, the method continues at 408. In some embodiments, the method continues at 410.

[0113] At 408, the method 400 determines a profile for a target vehicle speed and / or target torque distribution. For example, the PAC 124 determines the profile for the target vehicle speed and / or target torque distribution based on vehicle parameters as described, route characteristics, an energy consumption profile of the vehicle 10, other received information received from various components described herein. The profile for the target vehicle speed and / or target vehicle torque distribution corresponds to a vehicle speed and / or torque distribution that provides optimal or improved energy consumption efficiency of the vehicle 10 when implemented by the vehicle 10.

[0114] At 410, the method 400 generates a vehicle propulsion controller signal. For example, the PAC 124 is in direct communication with the VPC 102 and can provide a signal as an input to the VPC 102. The PAC 124 generates the vehicle propulsion controller signal based on the target vehicle speed. The vehicle propulsion controller signal can be referred to as a recommended target vehicle speed.

[0115] At 412, method 400 generates a torque split controller signal. For example, the PAC 124 may be in direct communication with the torque split controller 116 and may provide a signal as an input to the torque split controller 116. The PAC 124 generates the torque split controller signal based on the target torque split. The torque split controller signal may be referred to as a recommended target torque split.

[0116] At 414, method 400 provides a vehicle propulsion controller signal and a torque distribution controller signal. For example, the PAC 124 may provide the vehicle propulsion controller signal to the VPC 102. As described, the VPC 102 may determine whether to apply a target vehicle speed indicated by the vehicle propulsion controller signal. The PAC 124 may provide the torque distribution controller signal to the torque distribution controller 116, or may provide the torque distribution controller signal to the VPC 102, which may then provide the torque distribution signal to the torque distribution controller 116. As described, the torque distribution controller 116 may then determine whether to apply the torque distribution indicated by the torque distribution controller signal. The vehicle propulsion controller signal and the torque distribution controller signal correspond to a vehicle speed and / or torque distribution that, when implemented by the vehicle 10, provides optimal or improved energy consumption efficiency for the vehicle 10. For example, the PAC 124 may continuously update the target vehicle speed and / or target torque distribution as the vehicle 10 continues to traverse the route and based on updated traffic information, vehicle information, route information, other information, or a combination thereof.

[0117] Figure 7 is a flow chart generally illustrating an alternative vehicle propulsion control method 500 according to the principles of the present disclosure. At 502, the method 500 receives vehicle parameters. For example, the PAC 124 may receive various vehicle parameters of the vehicle 10 from any of the components described herein.

[0118] At 504, the method 500 determines a vehicle energy consumption profile. For example, the PAC 124 determines an energy consumption profile for the vehicle 10 using vehicle parameters and / or other route characteristics, such as historical route characteristics associated with routes previously traversed by the vehicle, route characteristics associated with routes previously traversed by similar vehicles (e.g., from the remote computing device 132 and / or the V2X communication module 130), other suitable route characteristics, or a combination thereof.

[0119] At 506, the method 500 receives route characteristics. For example, the PAC 124 receives various route characteristics (e.g., route characteristics of the route that the vehicle 10 is currently traversing or will traverse) and other information from any other components described herein. In some embodiments, the method continues at 508. In some embodiments, the method continues at 510.

[0120] At 508, the method 500 determines a target vehicle speed profile. For example, the PAC 124 determines the target vehicle speed profile based on vehicle parameters as described, route characteristics, an energy consumption profile of the vehicle 10, other received information received from various components described herein. The target vehicle speed profile corresponds to a vehicle speed that, when implemented by the vehicle 10, provides optimal or improved energy consumption efficiency of the vehicle 10.

[0121] At 510 , the method 500 generates a vehicle speed recommendation. For example, the PAC 124 generates the vehicle speed recommendation based on the target vehicle speed profile.

[0122] At 512, the method 500 provides a vehicle speed recommendation to the driver. For example, the PAC 124 may provide the vehicle speed recommendation to the driver of the vehicle 10 using the display 122, the mobile computing device, or other suitable device or display capable of providing the vehicle speed recommendation to the driver of the vehicle 10. For example, the driver of the vehicle 10 may comply with the vehicle speed recommendation or ignore the vehicle speed recommendation. The vehicle speed recommendation corresponds to a vehicle speed that provides optimal or improved energy efficiency for the vehicle 10 when implemented by the vehicle 10. For example, the PAC 124 may continuously update the profile of the target vehicle speed distribution as the vehicle 10 continues to traverse the route and based on updated traffic information, vehicle information, route information, other information, or a combination thereof.

[0123] Figure 8 is a flow chart generally illustrating a remaining vehicle battery range estimation method 600 according to the principles of the present disclosure. At 602, the method 600 identifies at least one route characteristic of a portion of a selected route. For example, the PAC 124 may identify at least one route characteristic of a portion of a selected route.

[0124] At 604, method 600 determines a vehicle energy consumption profile for the vehicle based at least on historical data indicating energy consumption of the vehicle for at least a portion of a route previously traversed by the vehicle, the at least a portion of the route having at least one route characteristic corresponding to at least one route characteristic of the portion of the selected route. For example, PAC 124 may determine a vehicle energy consumption profile for vehicle 10 based at least on historical data indicating energy consumption of the vehicle 10 for at least a portion of a route previously traversed by the vehicle 10, the at least a portion of the route having at least one route characteristic corresponding to at least one route characteristic of the portion of the selected route.

[0125] At 606 , the method 600 determines the current state of charge of the vehicle battery of the vehicle. For example, the PAC 124 may determine the current state of charge of the vehicle battery of the vehicle 10 .

[0126] At 608, method 600 determines a route energy consumption profile for the selected route based on at least one route characteristic of the portion of the selected route and the vehicle energy consumption profile. For example, the PAC 124 may determine a route energy consumption profile for the selected route based on at least one route characteristic of the portion of the selected route and the vehicle energy consumption profile.

[0127] At 610, method 600 calculates an estimated remaining charge of the vehicle battery at the end point of the selected route based on the vehicle battery's state of charge and the route energy consumption profile. For example, the PAC 124 may calculate an estimated remaining charge of the vehicle battery at the end point of the selected route based on the vehicle battery's state of charge and the route energy consumption profile.

[0128] At 612 , method 600 determines whether the estimated remaining charge of the vehicle battery is within a vehicle battery charge range. For example, the PAC 124 may determine whether the estimated remaining charge of the vehicle battery is within a vehicle battery charge range.

[0129] At 614 , method 600 generates a first indication in response to determining that the estimated remaining charge is within the vehicle battery charge range. For example, PAC 124 may generate a first indication in response to determining that the estimated remaining charge is within the vehicle battery charge range.

[0130] At 616, method 600 provides a first indication. For example, PAC 124 may provide the first indication.

[0131] Fig. 9is a flow chart generally illustrating an alternative remaining vehicle battery range estimation method 700 according to the principles of the present disclosure. At 702, the method 700 receives a minimum desired SoC at a destination, a minimum band and a maximum band around a speed limit, and an aggressiveness factor from the HMI control 104. For example, the PAC 124 may receive the minimum desired SoC at a destination, a minimum band and a maximum band around a speed limit, and an aggressiveness factor from the HMI control 104.

[0132] At 704, the method 700 receives a desired destination from the HMI control 104. For example, the PAC 124 may receive the desired destination from the HMI control 104.

[0133] At 706, method 700 selects a route to the desired destination. For example, the PAC 124 may select a route to the desired destination.

[0134] At 708 , the method 700 acquires route and vehicle characteristics (eg, dynamic and static). For example, the PAC 124 receives or retrieves route characteristics of the selected route and vehicle characteristics of the vehicle 10 , as described.

[0135] At 710, the method 700 determines an optimal speed profile to a desired destination to achieve a minimum desired SoC. For example, the PAC 124 may determine an optimal speed profile to a desired destination to achieve a minimum desired SoC.

[0136] At 712, the method 700 determines whether a solution exists, as described. For example, the PAC 124 may determine whether there is an optimal speed profile to the desired destination such that the minimum desired SoC is achievable. If yes, the method 700 continues at 716. If no, the method 700 continues at 714.

[0137] At 714, method 700 determines charging options where the vehicle can stop along the route for charging and provides these options to the driver of the vehicle. For example, PAC 124 can identify charging options along the route. PAC 124 can provide options to the driver via display 122 or other suitable display. Method 700 continues at 704.

[0138] At 716 , method 700 recommends that the driver travel along the defined route based on the defined target optimal speed profile. For example, the PAC 124 may recommend that the driver travel along the defined route based on the defined target optimal speed profile.

[0139] At 718 , the method 700 acquires the route and vehicle characteristics. For example, the PAC 124 may receive or retrieve updated route characteristics for the selected route and updated vehicle characteristics for the vehicle 10 .

[0140] At 720, the method 700 updates the estimated destination SoC based on the updated route and vehicle characteristics. For example, the PAC 124 may update the estimated destination SoC based on the updated route characteristics and the updated vehicle characteristics.

[0141] At 722, the method 700 determines whether the destination SoC is a deviation. For example, the PAC 124 may determine whether the destination SoC is a deviation. If yes, the method 700 continues at 724. If no, the method 700 returns to 718.

[0142] At 724, the method 700 updates to the optimal speed profile for the desired destination to achieve the desired SoC. For example, the PAC 124 may update to the optimal speed profile for the desired destination to achieve the desired SoC.

[0143] At 726, the method 700 determines whether a solution exists. For example, the PAC 124 can determine whether a solution exists, as described. If yes, the method 700 continues at 728. If no, the method 700 returns to 714.

[0144] The method 700 transitions to the updated target optimal speed profile at 728. For example, the PAC 124 may control propulsion of the vehicle 10 or recommend that the driver adhere to the updated target optimal speed profile.

[0145] Fig.10 8 is a flow chart generally illustrating an alternative remaining vehicle battery range estimation method 800 according to the principles of the present disclosure. At 802, the method 800 receives a minimum desired final SoC at a destination, a minimum band and a maximum band around a speed limit, and an aggressiveness factor from the HMI control 104. For example, the PAC 124 may receive the minimum desired final SoC at a destination, a minimum band and a maximum band around a speed limit, and an aggressiveness factor from the HMI control 104.

[0146] At 804, the method 800 receives a final destination and one or more waypoint destinations from the HMI control 104. For example, the PAC 124 may receive the final destination and one or more waypoint destinations from the HMI control 104.

[0147] At 806, method 800 selects a route based on the final destination and the one or more waypoint destinations. For example, the PAC 124 can select a route based on the final destination and the one or more waypoint destinations.

[0148] At 808 , method 800 acquires route and vehicle characteristics (eg, dynamic and static). For example, PAC 124 receives or retrieves route characteristics of the selected route and vehicle characteristics of vehicle 10 , as described.

[0149] At 810, method 800 determines an optimal speed profile based on the final destination and one or more waypoint destinations to achieve a minimum desired final SoC. For example, PAC 124 may determine an optimal speed profile based on the final destination and one or more waypoint destinations to achieve a minimum desired SoC.

[0150] At 812, the method 800 determines whether a solution exists, as described. For example, the PAC 124 can determine whether an optimal speed profile exists based on the final destination and one or more waypoint destinations such that the minimum desired final SoC is achievable. If yes, the method 800 continues at 816. If no, the method 800 continues at 814.

[0151] At 814, method 800 determines charging options where the vehicle can stop along the route for charging and provides these options to the driver of the vehicle. For example, PAC 124 can identify charging options along the route. PAC 124 can provide options to the driver via display 122 or other suitable display. Method 800 continues at 804.

[0152] At 816 , method 800 recommends that the driver travel along the defined route based on the defined target optimal speed profile. For example, the PAC 124 may recommend that the driver travel along the defined route based on the defined target optimal speed profile.

[0153] At 818 , the method 800 acquires the route and vehicle characteristics. For example, the PAC 124 may receive or retrieve updated route characteristics for the selected route and updated vehicle characteristics for the vehicle 10 .

[0154] At 820, the method 800 updates the estimated destination SoC based on the updated route and vehicle characteristics. For example, the PAC 124 may update the estimated destination SoC based on the updated route characteristics and the updated vehicle characteristics.

[0155] At 822, the method 800 determines whether the destination SoC is a deviation. For example, the PAC 124 can determine whether the destination SoC is a deviation. If yes, the method 800 continues at 824. If no, the method 800 returns to 818.

[0156] At 824, the method 800 updates to the optimal speed profile for the desired destination to achieve the desired final SoC. For example, the PAC 124 may update to the optimal speed profile for the desired destination to achieve the desired final SoC.

[0157] At 826, the method 800 determines whether a solution exists. For example, the PAC 124 can determine whether a solution exists, as described. If yes, the method 800 continues at 828. If no, the method 800 returns to 814.

[0158] The method 800 transitions to the updated target optimal speed profile at 828. For example, the PAC 124 may control propulsion of the vehicle 10 or recommend that the driver adhere to the updated target optimal speed profile.

[0159] Fig.11 is a flow chart generally illustrating an alternative remaining vehicle battery range estimation method 900 according to the principles of the present disclosure. At 902, the method 900 identifies at least one route characteristic of a portion of a selected route. For example, the PAC 124 may identify at least one route characteristic of a portion of a selected route.

[0160] At 904, method 900 determines a vehicle energy consumption profile for the vehicle based at least on historical data indicating energy consumption of the vehicle for at least a portion of a route previously traversed by the vehicle, the at least a portion of the route having at least one route characteristic corresponding to at least one route characteristic of the portion of the selected route. For example, PAC 124 may determine a vehicle energy consumption profile for vehicle 10 based at least on historical data indicating energy consumption of vehicle 10 for at least a portion of a route previously traversed by vehicle 10, the at least a portion of the route having at least one route characteristic corresponding to at least one route characteristic of the portion of the selected route.

[0161] At 906 , the method 900 determines a current state of charge of a vehicle battery of the vehicle. For example, the PAC 124 may determine a current state of charge of a vehicle battery of the vehicle 10 .

[0162] At 908, method 900 determines a route energy consumption profile for the selected route based on at least one route characteristic of a portion of the selected route and the vehicle energy consumption profile. For example, the PAC 124 may determine a route energy consumption profile for the selected route based on at least one route characteristic of a portion of the selected route and the vehicle energy consumption profile.

[0163] At 910, method 900 calculates an estimated remaining charge of the vehicle battery at the end of the selected route based on the vehicle battery's state of charge and the route energy consumption profile. For example, the PAC 124 may calculate an estimated remaining charge of the vehicle battery at the end of the selected route based on the vehicle battery's state of charge and the route energy consumption profile.

[0164] At 912 , method 900 determines whether the estimated remaining charge of the vehicle battery is within the vehicle battery range. For example, the PAC 124 may determine whether the estimated remaining charge of the vehicle battery is within the vehicle battery range.

[0165] At 914 , method 900 generates a first indication in response to determining that the estimated charge remaining is within the vehicle battery range. For example, the PAC 124 may generate the first indication in response to determining that the estimated charge remaining is within the vehicle battery range.

[0166] At 916, method 900, in response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range: (i) determines a target vehicle speed profile based on at least one route characteristic, a vehicle energy consumption profile, and a charge state of the vehicle battery; and (ii) generates a second indication. For example, PAC 124 may, in response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range: (i) determines a target vehicle speed profile based on at least one route characteristic, a vehicle energy consumption profile, and a charge state of the vehicle battery; and (ii) generates a second indication.

[0167] At 918, method 900 provides one of a first indication and a second indication. For example, PAC 124 may provide the first indication in response to determining that the estimated remaining charge is within the vehicle battery range, and provide the second indication in response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery range.

[0168] Fig.12 1 is a flow chart generally illustrating a vehicle propulsion control method 1000 according to the principles of the present disclosure. At 1002, the method 100 identifies at least one route characteristic of a portion of a most likely path. For example, the PAC 124 may identify at least one route characteristic of a portion of a most likely path.

[0169] At 1004, method 1000 determines a vehicle energy consumption profile for the vehicle based at least on historical data indicating energy consumption of the vehicle for at least a portion of a route previously traversed by the vehicle, the at least a portion of the route having at least one route characteristic corresponding to at least one route characteristic of a portion of a most probable path. For example, PAC 124 may determine a vehicle energy consumption profile for vehicle 10 based at least on historical data indicating energy consumption of vehicle 10 for at least a portion of a route previously traversed by vehicle 10, the at least a portion of the route having at least one route characteristic corresponding to at least one route characteristic of a portion of a most probable path.

[0170] At 1006, method 1000 determines a route energy consumption profile for the most likely path based on at least one route characteristic of a portion of the most likely path and the vehicle energy consumption profile. For example, PAC 124 may determine a route energy consumption profile for the most likely path based on at least one route characteristic of a portion of the most likely path and the vehicle energy consumption profile.

[0171] At 1008, the method 1000 determines a target vehicle speed profile based on the at least one route characteristic and the vehicle energy consumption profile. For example, the PAC 124 may determine the target vehicle speed profile based on the at least one route characteristic and the vehicle energy consumption profile.

[0172] At 1010, the method 1000 selectively controls vehicle propulsion based on the target vehicle speed profile. For example, the PAC 124 may selectively control vehicle propulsion based on the target vehicle speed profile.

[0173] Clause 1. A method for controlling propulsion of a vehicle, the method comprising: identifying at least one route characteristic of a portion of a most likely path; determining a vehicle energy consumption profile of the vehicle based at least on historical data, the historical data indicating energy consumption of the vehicle for at least a portion of a route previously traversed by the vehicle, the at least a portion of the route having at least one route characteristic corresponding to at least one route characteristic of a portion of the most likely path; determining a route energy consumption profile for the most likely path based on at least one route characteristic of a portion of the most likely path and the vehicle energy consumption profile; determining a target vehicle speed profile based on the at least one route characteristic and the vehicle energy consumption profile; and selectively controlling vehicle propulsion based on the target vehicle speed profile.

[0174] Clause 2. The method of claim 1, further comprising: determining a current state of charge of a vehicle battery of the vehicle.

[0175] Clause 3. The method of claim 2, further comprising: calculating an estimated remaining charge of a vehicle battery at the end of a most likely path based on the vehicle battery's charge state and a route energy consumption profile; and determining whether the estimated remaining charge of the vehicle battery is within the vehicle battery charge range.

[0176] Clause 4. The method of claim 3, further comprising: generating a first indication in response to determining that the estimated remaining charge is within the vehicle battery charge range.

[0177] Clause 5. The method of claim 4, further comprising: in response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range, generating a second indication; and providing one of the first indication and the second indication.

[0178] Clause 6. The method of claim 5, wherein the target vehicle speed profile is determined in response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range and further based on a charge state of the vehicle battery.

[0179] Clause 7. The method of claim 5, wherein the first indication comprises an estimated remaining charge of a vehicle battery at the end of the most likely path.

[0180] Clause 8. The method of claim 5, characterized in that the second indication includes a warning indicating that the vehicle battery may be depleted before the vehicle reaches the end of the most likely path, and a recommendation to follow a target vehicle speed profile to avoid depleting the vehicle battery before the vehicle reaches the end of the most likely path.

[0181] Clause 9. The method of claim 5, wherein providing one of the first indication and the second indication comprises providing one of the first indication and the second indication at a display of a vehicle.

[0182] Clause 10. The method of claim 5, wherein providing one of the first indication and the second indication comprises providing one of the first indication and the second indication at a mobile computing device.

[0183] Clause 11. The method of claim 5, wherein providing one of the first indication and the second indication comprises providing one of the first indication and the second indication to an autonomous controller of a vehicle.

[0184] Clause 12. The method of claim 1, wherein the at least one route characteristic comprises at least one of traffic conditions, traffic signals, and road grade.

[0185] Clause 13. A system for controlling propulsion of a vehicle, the system comprising: a processor; and a memory, the memory comprising instructions, which, when executed by the processor, cause the processor to: identify at least one route characteristic of a portion of a most likely path; determine a vehicle energy consumption profile for the vehicle based at least on historical data, the historical data indicating energy consumption of the vehicle for at least a portion of a route previously traversed by the vehicle, the historical data having at least one route characteristic corresponding to at least one route characteristic of a portion of the most likely path; determine a route energy consumption profile for the most likely path based on at least one route characteristic of a portion of the most likely path and the vehicle energy consumption profile; determine a target vehicle speed profile based on at least one route characteristic and the vehicle energy consumption profile; and selectively control vehicle propulsion based on the target vehicle speed profile.

[0186] Clause 14. The system of claim 13, wherein the instructions further cause the processor to: determine a current state of charge of a vehicle battery of the vehicle.

[0187] Clause 15. The system of claim 14, characterized in that the instructions further cause the processor to: calculate an estimated remaining charge of the vehicle battery at the end of the most likely path based on the charge state of the vehicle battery and the route energy consumption profile; and determine whether the estimated remaining charge of the vehicle battery is within the vehicle battery charge range.

[0188] Clause 16. The system of claim 15, wherein the instructions further cause the processor to: generate a first indication in response to determining that the estimated remaining charge is within the vehicle battery charge range.

[0189] Clause 17. The system of claim 16, wherein the instructions further cause the processor to: in response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range, generate a second indication; and provide one of the first indication and the second indication.

[0190] Clause 18. The system of claim 17, wherein the target vehicle speed profile is determined in response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range and further based on a charge state of the vehicle battery.

[0191] Clause 19. The system of claim 17, wherein the first indication includes an estimated remaining charge of a vehicle battery at the end of the most likely path, and wherein the second indication includes a warning indicating that the vehicle battery may be depleted before the vehicle reaches the end of the most likely path, and a recommendation to follow a target vehicle speed profile to avoid depleting the vehicle battery before the vehicle reaches the end of the most likely path.

[0192] Clause 20. A non-transitory computer-readable storage medium comprising executable instructions that, when executed by a processor, facilitate the performance of operations, the operations comprising: identifying at least one route characteristic of a portion of a most likely path; determining a vehicle energy consumption profile for a vehicle based at least on historical data indicating energy consumption of the vehicle for at least a portion of a route previously traversed by the vehicle, the at least a portion of the route having at least one route characteristic that corresponds to at least one route characteristic of a portion of the most likely path; determining a current state of charge of a vehicle battery of the vehicle; based on at least one route characteristic and a vehicle energy consumption profile of a portion of a most likely path, determining a route energy consumption profile for the most likely path; calculating an estimated remaining charge of the vehicle battery at the end of the most likely path based on the charge state of the vehicle battery and the route energy consumption profile; determining whether the estimated remaining charge of the vehicle battery is within the vehicle battery charge range; in response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range, determining a target vehicle speed profile based on at least one route characteristic, the vehicle energy consumption profile and the charge state of the vehicle battery; and generating an indication; and providing the indication.

[0193] The above discussion is intended to illustrate the principles and embodiments of the present invention. Once the above disclosure is fully appreciated, numerous variations and modifications will become apparent to those skilled in the art. The appended claims are intended to be interpreted as including all such variations and modifications.

[0194] The word "example" is used herein to mean used as an example, instance, or illustration. Any aspect or design described as an "example" herein is not necessarily to be interpreted as being preferred or advantageous over other aspects or designs. On the contrary, the use of the word "example" is intended to present concepts in a specific way. As used in this application, the term "or" is intended to mean an inclusive "or" rather than an exclusive "or". That is, unless otherwise specified or clear from the context, "X includes A or B" is intended to mean any one of the natural inclusive arrangements. That is, if X includes A; X includes B; or X includes both A and B, then "X includes A or B" is satisfied in any of the aforementioned examples. In addition, the article "a / an" as used in this application and the appended claims should generally be interpreted as meaning "one or more", unless otherwise specified or clear from the context to refer to the singular form. Moreover, the use of the term "implementation" or "an implementation" throughout the text is not intended to mean the same embodiment or implementation, unless described as such.

[0195] The systems, algorithms, methods, instructions, etc. described herein may be implemented in hardware, software, or any combination thereof. Hardware may include, for example, a computer, an intellectual property (IP) core, an application specific integrated circuit (ASIC), a programmable logic array, an optical processor, a programmable logic controller, microcode, a microcontroller, a server, a microprocessor, a digital signal processor, or any other suitable circuit. In the claims, the term "processor" should be understood to cover any of the foregoing hardware, whether singly or in combination. The terms "signal" and "data" are used interchangeably.

[0196] As used herein, the term module may include a packaged functional hardware unit designed for use with other components, a set of instructions executable by a controller (e.g., a processor executing software or firmware), a processing circuit system configured to perform a specific function, and a self-contained hardware or software component that interacts with a larger system. For example, a module may include an application specific integrated circuit (ASIC); a field programmable gate array (FPGA); an electrical circuit; a digital logic circuit; an analog circuit; a combination of discrete circuits, gates, and other types of hardware; or a combination thereof. In other embodiments, a module may include a memory that stores instructions executable by a controller to implement the features of the module.

[0197] Further, in one aspect, for example, a general-purpose computer or general-purpose processor may be used to implement the system described herein, which has a computer program that implements the corresponding methods, algorithms and / or instructions described herein when executed. Additionally or alternatively, for example, a special-purpose computer / processor may be utilized, which may include other hardware for implementing any of the methods, algorithms or instructions described herein.

[0198] Further, all or part of the implementation of the present disclosure may take the form of a computer program product accessible from, for example, a computer-usable or computer-readable medium. A computer-usable or computer-readable medium may be any device that may, for example, tangibly contain, store, transmit, or transfer a program for use by or in conjunction with any processor. The medium may be, for example, an electronic device, a magnetic device, an optical device, an electromagnetic device, or a semiconductor device. Other suitable media are also available.

[0199] The embodiments, implementations and aspects described above have been described to allow easy understanding of the invention and do not limit the invention. On the contrary, the invention is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims, the scope of which should be given the broadest interpretation to cover all such modifications and equivalent structures as permitted under the law.

Claims

1. A method for controlling propulsion of a vehicle, the method comprising: identifying at least one route characteristic of a portion of a most likely path; determining a vehicle energy consumption profile for a vehicle based at least on historical data indicating energy consumption of the vehicle for at least a portion of a route previously traversed by the vehicle, the at least a portion of the route having at least one route characteristic corresponding to the at least one route characteristic of a portion of the most probable path; determining a route energy consumption profile for the most probable path based on the at least one route characteristic of a portion of the most probable path and the vehicle energy consumption profile; determining a target vehicle speed profile based on the at least one route characteristic and the vehicle energy consumption profile; as well as Vehicle propulsion is selectively controlled based on the target vehicle speed profile.

2. The method of claim 1, further comprising: A current state of charge of a vehicle battery of the vehicle is determined.

3. The method of claim 2, further comprising: calculating an estimated remaining charge of the vehicle battery at the end of the most likely path based on the state of charge of the vehicle battery and the route energy consumption profile; and A determination is made as to whether the estimated remaining charge of the vehicle battery is within a vehicle battery charge range.

4. The method of claim 3, further comprising: In response to determining that the estimated remaining charge is within the vehicle battery charge range, a first indication is generated.

5. The method of claim 4, further comprising: In response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range: generating a second indication; and One of the first indication and the second indication is provided.

6. The method according to claim 5, characterized in that The target vehicle speed profile is determined in response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range and further based on the state of charge of the vehicle battery.

7. The method according to claim 5, characterized in that The first indication includes the estimated remaining charge of the vehicle battery at the end of the most likely path.

8. The method according to claim 5, characterized in that The second indication includes a warning indicating that the vehicle battery may be depleted before the vehicle reaches the end of the most probable path and a recommendation to follow the target vehicle speed profile to avoid depleting the vehicle battery before the vehicle reaches the end of the most probable path.

9. The method according to claim 5, characterized in that Providing the one of the first indication and the second indication includes providing the one of the first indication and the second indication at a display of the vehicle.

10. The method according to claim 5, characterized in that Providing the one of the first indication and the second indication includes providing the one of the first indication and the second indication at a mobile computing device.

11. The method according to claim 5, characterized in that Providing the one of the first indication and the second indication includes providing the one of the first indication and the second indication to an autonomous controller of the vehicle.

12. The method according to claim 1, characterized in that The at least one route characteristic includes at least one of traffic conditions, traffic signals, and road slope.

13. A system for controlling propulsion of a vehicle, the system comprising: processor; as well as a memory comprising instructions that, when executed by the processor, cause the processor to: identifying at least one route characteristic of a portion of a most likely path; determining a vehicle energy consumption profile for a vehicle based at least on historical data indicating energy consumption of the vehicle for at least a portion of a route previously traversed by the vehicle, the at least a portion of the route having at least one route characteristic corresponding to the at least one route characteristic of a portion of the most probable path; determining a route energy consumption profile for the most probable path based on the at least one route characteristic of a portion of the most probable path and the vehicle energy consumption profile; determining a target vehicle speed profile based on the at least one route characteristic and the vehicle energy consumption profile; as well as Vehicle propulsion is selectively controlled based on the target vehicle speed profile.

14. The system of claim 13, wherein: The instructions further cause the processor to determine a current state of charge of a vehicle battery of the vehicle.

15. The system of claim 14, wherein: The instructions further cause the processor to: calculating an estimated remaining charge of the vehicle battery at the end of the most likely path based on the state of charge of the vehicle battery and the route energy consumption profile; and A determination is made as to whether the estimated remaining charge of the vehicle battery is within a vehicle battery charge range.

16. The system of claim 15, wherein: The instructions further cause the processor to generate a first indication in response to determining that the estimated remaining charge is within the vehicle battery charge range.

17. The system of claim 16, wherein: The instructions further cause the processor to: in response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range: generating a second indication; and One of the first indication and the second indication is provided.

18. The system of claim 17, wherein: The target vehicle speed profile is determined in response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range and further based on the state of charge of the vehicle battery.

19. The system of claim 17, wherein: The first indication includes the estimated remaining charge of the vehicle battery at the end of the most likely path, and wherein the second indication includes a warning indicating that the vehicle battery may be depleted before the vehicle reaches the end of the most likely path, and a recommendation to follow the target vehicle speed profile to avoid depleting the vehicle battery before the vehicle reaches the end of the most likely path.

20. A non-transitory computer-readable storage medium comprising executable instructions that, when executed by a processor, facilitate performance of operations comprising: identifying at least one route characteristic of a portion of a most likely path; determining a vehicle energy consumption profile for a vehicle based at least on historical data indicating energy consumption of the vehicle for at least a portion of a route previously traversed by the vehicle, the at least a portion of the route having at least one route characteristic corresponding to the at least one route characteristic of a portion of the most probable path; determining a current state of charge of a vehicle battery of the vehicle; determining a route energy consumption profile for the most probable path based on the at least one route characteristic of a portion of the most probable path and the vehicle energy consumption profile; calculating an estimated remaining charge of the vehicle battery at an end of the most likely path based on the state of charge of the vehicle battery and the route energy consumption profile; determining whether the estimated remaining charge of the vehicle battery is within a vehicle battery charge range; In response to determining that the estimated remaining charge is less than a lower limit of the vehicle battery charge range, determining a target vehicle speed profile based on the at least one route characteristic, the vehicle energy consumption profile, and the state of charge of the vehicle battery; as well as Generate instructions; as well as The instructions are provided.

Images