Control system and method for a vehicle system

Abstract

A system and method for generating a trip plan for a vehicle system along a route. Engine usage during the trip is determined based on engine operating parameters, energy storage device operating parameters, and one or more desired objectives of the trip. Energy storage device usage during the trip is also determined based on the engine operating parameters, the energy storage device operating parameters, and the one or more objectives, including when to charge or discharge the energy storage device during the trip.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. non-provisional patent application No. 16 / 722,323, filed December 20, 2019, entitled "Control System and Method for a Vehicle System," and U.S. provisional patent application No. 62 / 880,926, filed July 31, 2019, entitled "System and Method for Controlling a Vehicle System to Achieve an Objective During a Journey," the entire disclosure of which is incorporated herein by reference. Technical Field

[0003] The embodiments of the subject matter described herein relate to controlling the movement of a vehicle system. Background Technology

[0004] A vehicle system traveling along a route can travel from a starting point (or departure location) to a destination (or arrival location) according to a defined itinerary. Each trip can extend a considerable distance along the route and may include one or more designated stops along the route before reaching the arrival location. These designated stops can be used for crew changes, refueling, passenger pick-up and / or cargo loading and unloading, etc. Some vehicle systems travel according to a itinerary plan, which provides the vehicle system with instructions to execute during the vehicle system's movement, causing the vehicle system to meet or achieve certain objectives during the trip. Trip objectives may include: reaching the arrival location at or before a predetermined arrival time, increasing fuel efficiency (relative to the fuel efficiency of a vehicle system not following a itinerary plan), complying with speed limits and emission limits, etc. A itinerary plan can be generated to achieve specific objectives, and therefore the instructions provided by the itinerary plan are based on these specific objectives.

[0005] Hybrid vehicles, or vehicles combining an internal combustion engine and a battery-powered engine, can involve numerous considerations regarding how they operate and when they should stop during a trip. For example, where the number of roadside charging stations is limited, it's necessary to determine when the vehicle should stop at such stations. For battery-powered hybrid vehicles, the distance the vehicle can travel must be determined based on variables such as weather, wind, speed limits, vehicle weight, stopping point, and starting point before it must stop at a roadside charging station. Similarly, the amount of electricity provided (including the time spent recharging the battery) directly affects the duration of the trip. Therefore, trip planning is required to account for the variables associated with either battery-powered or battery-powered hybrid vehicles.

[0006] Additionally, when considering long-distance travel using hybrid vehicles, it may be necessary to determine when and how the battery should supplement the prime mover of the mechanical power source. In one instance, a greedy algorithm could be used to determine when to charge and discharge the battery at a specified C-rate. However, depending on the different variables associated with the trip, using a greedy algorithm may not achieve the desired trip planning.

[0007] Some control systems used in vehicle systems (e.g., Wabtec's TRIP OPTIMIZER) TM Energy management systems can reduce braking energy and thus save fuel by controlling the operation of vehicle systems. Nevertheless, sufficient braking energy exists to offer significant opportunities for fuel savings in hybrid vehicle systems. In addition to this efficiency advantage, adding batteries can provide benefits such as reduced emissions (e.g., zero emissions in green zones) or improved throughput, thereby shortening travel time. However, significant challenges arise from the impact of charging and discharging conditions on battery life due to capacity degradation. Capacity degradation coupled with the high cost of battery replacement makes hybrid vehicles a less viable option than conventional vehicles. Summary of the Invention

[0008] According to one embodiment, a method can be provided, the method comprising: obtaining specified operating settings for moving a vehicle system along one or more routes to drive the vehicle system to achieve one or more objectives; and determining operating parameters of an engine and an energy storage device. The engine usage during the trip can be determined based on the engine operating parameters, the energy storage device operating parameters, and the one or more objectives. The energy storage device usage during the trip can also be determined based on the engine operating parameters, the energy storage device operating parameters, and the one or more objectives, including when the energy storage device is charged or discharged during the trip.

[0009] According to one embodiment, a system can be provided comprising a controller configured to specify one or more operating settings for a vehicle at one or more locations, at different times, or at different distances along one or more routes. These one or more operating settings are specified to drive the vehicle to achieve one or more objectives during the journey by controlling the use of the vehicle's engine and energy storage device during the journey. Both the engine and the energy storage device operate to propel the vehicle during the journey, and the engine usage during the journey is based on engine operating parameters, energy storage device operating parameters, and the one or more objectives. The energy storage device usage during the journey may be based on the engine operating parameters, the energy storage device operating parameters, and the one or more objectives, including when to charge or discharge the energy storage device during the journey.

[0010] According to one embodiment, a method can be provided comprising: obtaining specified operating settings for moving a vehicle system along one or more routes to drive the vehicle system to achieve one or more objectives; and determining operating parameters of an engine and an energy storage device. The efficiency of the engine during the journey can be determined based on the engine operating parameters, the energy storage device operating parameters, and the one or more objectives. The usage of the energy storage device during the journey can also be determined based on the engine operating parameters, the energy storage device operating parameters, and the one or more objectives, including when to charge or discharge the energy storage device during the journey. The usage of the energy storage device may include changing the C-rate of the vehicle's battery based on the determined engine efficiency. Attached Figure Description

[0011] Referring to the accompanying drawings, the subject matter of the invention can be understood by reading the following description of non-limiting embodiments, in which:

[0012] Figure 1 This is a schematic diagram of one embodiment of a control system installed on a vehicle system;

[0013] Figure 2 It is based on the controller's schematic diagram;

[0014] Figure 3 This is a schematic diagram of the propulsion subsystem;

[0015] Figure 4 This is a schematic diagram of one embodiment of a vehicle system;

[0016] Figure 5This is a flowchart of an embodiment of a method for controlling a vehicle system traveling on a route;

[0017] Figure 6 This is a schematic diagram of an embodiment of a route planning algorithm;

[0018] Figure 7A It is a graph showing the fuel savings resulting from proportional life factor adjustments.

[0019] Figure 7B It is a graph of the proportional life coefficient and the fuel savings of proportional adjustment;

[0020] Figure 8A It is a graph of distance relative to velocity;

[0021] Figure 8B It is a graph of distance versus fuel ratio;

[0022] Figure 9A It is a graph of distance relative to the proportional engine power;

[0023] Figure 9B It is a graph showing the relationship between distance and proportional battery power;

[0024] Figure 9C It is a graph of distance versus battery temperature, voltage, and state of charge (SOE);

[0025] Figure 9D It is a graph of distance versus proportional temperature;

[0026] Figure 9E It is a graph of distance relative to SOE dynamics;

[0027] Figure 9F It is a graph of distance relative to a proportional temperature; and

[0028] Figure 10 This is a flowchart of one embodiment of a method for dynamically controlling the C-rate of a battery. Detailed Implementation

[0029] The embodiments of the subject matter described herein relate to a hybrid propulsion-generating vehicle, which includes a control system that manages the flow of power between the vehicle's engine and battery. The control system enhances engine fuel economy by managing this flow while mitigating battery aging by operating the battery under defined charge / discharge conditions. In one example, the energy management of the control system can leverage railway-specific features, such as the availability of track and trip planning information. The control system also solves a multi-objective optimization problem that reduces the weighted sum of fuel and battery degradation during a trip to determine predicted engine and battery power for a given trip. For this purpose, battery aging can be predicted using a battery life model and a reduced-order battery thermal model. This facilitates optimal decision-making that simultaneously extends battery life and enhances battery performance.

[0030] Figure 1 A schematic diagram of a control system 100 according to an embodiment is shown. The control system may be mounted on a vehicle system 102. The vehicle system may be configured to travel along route 104 from a starting point (or departure position) to a destination (or arrival position). The vehicle system includes a propulsion-generating vehicle 108 and a non-propulsion-generating vehicle 110 mechanically interconnected to travel together along the route. The vehicle system may include at least one propulsion-generating vehicle and optionally one or more non-propulsion-generating vehicles. In one example, a single vehicle may be a hybrid truck with a dual-fuel engine.

[0031] A propulsion-generating vehicle can be configured to generate traction to propel (e.g., pull or push) a non-propulsion-generating vehicle. The propulsion-generating vehicle includes a propulsion subsystem comprising one or more traction motors that generate traction to propel the vehicle system. The propulsion-generating vehicle also includes a braking system 112 that generates braking force to decelerate or stop the propulsion-generating vehicle itself. Optionally, a non-propulsion-generating vehicle includes a braking system but does not include a propulsion subsystem. A propulsion-generating vehicle may be referred to herein as a propulsion vehicle, and a non-propulsion-generating vehicle may be referred to herein as a carriage. Although Figure 1The diagram illustrates a propulsion vehicle and a carriage, but a vehicle system may comprise multiple propulsion vehicles and / or multiple carriages. In an alternative embodiment, the vehicle system comprises only a propulsion vehicle, such that the propulsion vehicle is not coupled to a carriage or another vehicle.

[0032] The control system controls the movement of the vehicle system. In the illustrated embodiment, the control system may be entirely mounted on the propulsion vehicle. However, in other embodiments, one or more components of the control system may be distributed across several vehicles, such as those constituting the vehicle system. For example, some components may be distributed across two or more propulsion vehicles coupled together in groups or constituencies. In alternative embodiments, at least some components of the control system may be located remotely from the vehicle system, such as at a dispatch location. The remote components of the control system may communicate with the vehicle system (and with the components of the control system mounted thereon).

[0033] In the illustrated embodiments, the vehicle system may be a rail vehicle system, and the route may be a railway track formed by one or more tracks. The propulsion vehicle may be a locomotive, and the carriages may be railcars carrying passengers and / or goods. Alternatively, the propulsion vehicle may be another type of rail vehicle besides a locomotive. In alternative embodiments, the vehicle system may be one or more automobiles, ships, aircraft, mining vehicles, agricultural vehicles, or other off-highway vehicle (OHV) systems (e.g., vehicle systems that are legally prohibited and / or not designed for use on public roads). While some examples provided herein describe routes as railway tracks, not all embodiments are limited to rail vehicles traveling on railway tracks. One or more embodiments may be used in combination with non-rail vehicles and routes other than railway tracks, such as roads, paths, waterways, etc.

[0034] exist Figure 1 In the example, each vehicle in the vehicle system includes multiple wheels 120 that engage the route and at least one axle 122 that couples the left and right wheels together. Figure 1(Only the left wheel is shown in the diagram). Optionally, the wheel and axle are located on one or more bogies 118. Optionally, the bogie can be a fixed-axle bogie, such that the wheels are rotatably fixed to the axle, so that the left wheel rotates at the same speed, with the same amount of rotation, and at the same time as the right wheel. Vehicles in a vehicle system can be mechanically coupled to each other, such as by a coupler. For example, a propulsion vehicle can be mechanically coupled to a vehicle via coupler 123.

[0035] The coupler may have a traction device configured to absorb compressive and tensile forces to reduce slack between the vehicles. Although in Figure 1 Not shown, but the propulsion vehicle may have a coupler located at the rear of the propulsion vehicle and / or the carriage may have a coupler located at the front of the carriage, to mechanically couple the respective vehicle to other vehicles in the vehicle system. Alternatively, the vehicles in the vehicle system may not be mechanically coupled to each other, but may be logically coupled to each other. For example, vehicles may be logically coupled to each other by communicating with each other to coordinate the movement of the vehicles, so that multiple vehicles can travel together as a vehicle system in a convoy or group.

[0036] The control system may further include a wireless communication system 126, which allows wireless communication between vehicles in the vehicle system and / or with a remote location, which may be a remote (dispatch) location 128. The communication system may include a receiver and a transmitter, or a transceiver performing both receiving and transmitting functions. The communication system may also include an antenna and associated circuitry.

[0037] The control system further includes a travel characterization element 130. The travel characterization element can be configured to provide information about the travel of the vehicle system along a route. The travel information may include route characteristics, designated locations, designated stopping locations, planned times, meeting events, direction along the route, etc.

[0038] For example, specified route characteristics may include gradient, elevation slowwarnings, environmental conditions (e.g., rain and snow), and curvature information. Specified locations may include roadside installations, passing loops, refueling stations, passenger transfer stations, crew and / or cargo transfer stations, and the origin and destination of the journey. At least some of the specified locations may be designated stop locations, where the vehicle system can be scheduled to complete a stop within a certain timeframe. For example, a passenger transfer station may be a designated stop location, while a roadside installation may be a designated location outside of a stop location. Roadside installations can be used to check the punctuality of the vehicle system by comparing the actual time the vehicle system takes to pass a designated roadside installation along the route with the estimated time the vehicle system will take to pass the roadside installation according to the journey schedule.

[0039] Trip information regarding planned times can include departure and arrival times for the entire trip, times to and / or arrival times at designated locations, rest periods (e.g., the time a vehicle system can dock), and departure times at each designated stop during the trip. Meeting events include locations along loops and timings of passing through or being passed by another vehicle system on the same route. The direction along the route is the direction used to traverse the route to reach the destination or arrival location. The direction can be updated to provide routes around congested areas, construction areas, or maintenance areas.

[0040] The travel characterization element can be a database stored in an electronic storage device or memory. Information in the travel characterization element 130 can be input by an operator through a user interface device, can be automatically uploaded, or can be received remotely through a communication system. At least some of the information in the travel characterization element can originate from travel lists, logs, etc.

[0041] In one embodiment, the control system may include a vehicle characterization element 134. The vehicle characterization element can provide information about the composition of the vehicle system, such as the type of carriages (e.g., manufacturer, product number, material, etc.), the number of carriages, the weight of the carriages, whether the carriages are consistent (meaning the weight and distribution along the length of the entire vehicle system are relatively the same) or inconsistent, the type and weight of the cargo, the total weight of the vehicle system, the number of propelled vehicles, the position and arrangement of the propelled vehicles relative to the carriages, and the type of propelled vehicles (including manufacturer, product number, power output capacity, available notch settings, fuel usage, etc.).

[0042] Vehicle characterization elements can be databases stored in electronic storage devices or memory. Information in vehicle characterization elements can be input by an operator using input / output (I / O) devices (referred to as user interface devices), can be automatically uploaded, or can be received remotely via a communication system. At least some of the information in vehicle characterization elements can originate from vehicle inventory lists, logs, etc.

[0043] The control system has a controller 136 or a control unit, which can be a hardware and / or software system operating to perform one or more functions of the vehicle system. The controller receives information from components of the control system, analyzes the received information, and generates operating settings for the vehicle system to control its movement. The operating settings may be included in a trip plan. The controller can access the positioner device 124 (…). Figure 2 ( ), vehicle characterizing elements, travel characterizing elements, and other sensors 132 on the vehicle system, or receiving information from them.

[0044] Figure 2 A schematic diagram of a controller is provided, which can be configured to control the operation of a propulsion vehicle. The controller may be a device that internally (e.g., within a housing) contains one or more processors 138. Each processor may contain a microprocessor or an equivalent control circuitry system. At least one algorithm runs within the one or more processors. For example, the one or more processors may run according to one or more algorithms to generate a travel plan.

[0045] The controller may optionally include a controller memory 140, which may be an electronic, computer-readable storage device or medium. The controller memory may be located within the controller housing or, alternatively, on a separate device communicatively coupled to the controller and the one or more processors therein. "Communicatively coupled" means that two devices, systems, subsystems, assemblies, modules, components, etc., are joined via one or more wired or wireless communication links, such as via one or more conductive (e.g., copper) wires, cables, or buses; wireless networks; fiber optic cables, etc. The controller memory may contain a tangible, non-transitory, computer-readable storage medium that temporarily or permanently stores data for use by one or more processors. The memory may contain one or more volatile and / or non-volatile memory devices, such as random access memory (RAM), static random access memory (SRAM), dynamic RAM (DRAM), another type of RAM, read-only memory (ROM), flash memory, magnetic storage devices (e.g., hard disks, floppy disks, or magnetic tapes), optical disks, etc.

[0046] The controller may also include a battery regulator unit 141, which may contain a battery model for calculating battery C-rate, battery life, battery state, battery thermal properties, power boost for providing additional battery replenishment, battery charging, etc. The battery C-rate is a measure of the rate at which the battery can be charged or discharged. Therefore, the C-rate can be a measure of energy usage or energy consumption. It can be measured by dividing the current flowing through the battery by the theoretical current consumption, at which the battery will deliver its nominal rated capacity, expressed as 1 / hour, in one hour. Battery aging is the amount of energy storage capacity lost by the battery and can be measured in megawatt-hours (MWH). Additionally, information and data determined or derived by the one or more processors, trip characterization elements, other sensors, such as GPS sensors and other positioning devices, vehicle characterization elements, battery regulator unit, etc., can be stored in the controller memory for subsequent processing. By using, collecting, and processing the information and data, the controller can determine the operating settings of one or more vehicles for the trip plan.

[0047] Operating settings can be one or more of the following implemented by the vehicle system during a journey: speed, throttle setting, braking setting, charge rate setting, discharge rate setting, or acceleration. Battery charge rate is a measure of the rate at which a battery can be charged or discharged. It can be measured by dividing the current flowing through the battery by the theoretical current consumption, at which the battery will deliver its nominal rated capacity, expressed in units of 1 / hour, per hour. Battery discharge amount is the amount of charge applied to a battery that has already been discharged. Discharge settings may include the amperes used by the energy storage device.

[0048] Optionally, the controller can be configured to transmit at least some of the operating settings specified by the controller via control signals. The control signals can be directed to the user interface devices of the propulsion subsystem, braking subsystem, or vehicle system. For example, the control signals can be directed to the propulsion subsystem and may include notch throttle settings for the propulsion subsystem's traction motor to be autonomously implemented upon receiving the control signals.

[0049] In another example, control signals may be directed to a user interface device that displays and / or otherwise presents information to a human operator of the vehicle system. The control signals transmitted to the user interface device may include throttle settings for controlling the throttle of the propulsion subsystem. The control signals may also include data for visually displaying the throttle settings on the display of the user interface device and / or for audibly warning the operator using the speaker of the user interface device. Optionally, the throttle settings may be presented to the operator as a suggestion for the operator to decide whether to implement the suggested throttle settings.

[0050] Figure 3 Showing Figure 1 A schematic diagram of the propulsion subsystem 142 of the propulsion vehicle. Again, although... Figure 1 An example embodiment of a rail-based vehicle is shown, but other examples provide other vehicles, including automobiles, dual-fuel trucks, off-highway vehicles, mining vehicles, road construction vehicles, etc. Specifically, the propulsion subsystem can be an example propulsion subsystem of any of these vehicles. The propulsion subsystem may include an engine 144, which includes a prime mover 146, which can be coupled to a transmission 148 and provides mechanical input 147 to the transmission to drive a shaft. In examples, the engine may be an internal combustion engine, an electric motor, a diesel engine, a hydraulic engine, etc. Similarly, the transmission may be a mechanical transmission, an electric transmission, a hydraulic transmission, etc.

[0051] The propulsion subsystem may also include an energy storage device 150 coupled to a transmission that allows the energy storage device to also drive the shaft of the propulsion vehicle. In one example, the energy storage device may be a battery. Specifically, the energy storage device is capable of providing energy and also storing energy. While batteries provide electrical energy through chemical processes that can be discharged, charged, and stored, in other examples, the energy storage device may store chemical energy, mechanical energy, etc., through other processes. The controller may operate the propulsion subsystem such that only the engine drives the shaft, only the energy storage device drives the shaft, or the engine and energy storage device can drive the shaft in parallel, such that the energy storage device supplements the engine to provide power to the shaft. The controller may be configured to control the operation of the energy storage device, including determining when to charge and discharge the energy storage device during travel. In one example, the controller may also be configured to control the operation of the propulsion vehicle to maintain the temperature of the energy storage device below a threshold temperature.

[0052] The propulsion subsystem may optionally include a braking system comprising an electrical bus 154 for charging the energy storage device. Specifically, during dynamic braking, electricity can be generated by producing torque through the traction motor to decelerate the vehicle. Thus, in an example embodiment, when the energy storage device may be a battery, the generated electricity can be transferred from the traction motor to the battery via the electrical bus to recharge the battery. In this way, when such a vehicle may be traversing an uphill section, such as a hillside, the battery can increase its discharge rate to supplement the engine, and then the battery can be recharged through the braking system when the vehicle is traversing a downhill section or hillside using the braking system. In one instance, by increasing the battery discharge rate, the power generated uphill may be greater than that of a non-hybrid-based system.

[0053] Figure 4 A schematic diagram illustrating an alternative embodiment of a vehicle system 400 is shown, the vehicle system having a first vehicle 402 and a second vehicle 404, both of which may be propulsion vehicles. The first vehicle includes a first propulsion subsystem 406, which includes a first engine 408 having a first prime mover 410. The first prime mover may be coupled to a first transmission 414 and provides a first mechanical input 412 to the first transmission to drive a first shaft 416 of the first vehicle. In one example, the first engine may be an internal combustion engine. In another example, the first engine operates using diesel fuel.

[0054] The propulsion subsystem also includes a first energy storage device 418, which is coupled to a first transmission device, thereby allowing the first energy storage device to also drive the first shaft of the first vehicle. In one example, the first energy storage device may be a battery. Specifically, the energy storage device is capable of providing energy and also storing energy. While batteries provide electrical energy through chemical processes that can be discharged, charged, and stored, in other examples, the energy storage device may store chemical energy, mechanical energy, etc., through other processes.

[0055] The controller 420 can operate the first propulsion subsystem such that only the first engine drives the first shaft, only the first energy storage device drives the first shaft, or the first engine and the first energy storage device can drive the first shaft in parallel, such that the first energy storage device supplements the first engine to provide power to the first shaft.

[0056] The second vehicle similarly includes a second propulsion subsystem 422, which includes a second engine 424. The second engine includes a second prime mover 426, which can be coupled to a second transmission 430 and provides a second mechanical input 428 to the second transmission to drive the second shaft 432 of the second vehicle. In one example, the second engine may be an internal combustion engine. In another example, the second engine operates using diesel fuel. The propulsion subsystem also includes a second energy storage device 434, which is coupled to the second transmission, allowing the second energy storage device to also drive the second shaft of the second vehicle. In one example, the energy storage device may be a battery. The controller can operate the second propulsion subsystem such that only the second engine drives the second shaft, only the second energy storage device drives the second shaft, or the second engine and the second energy storage device can drive the second shaft in parallel, such that the second energy storage device supplements the second engine to power the second shaft.

[0057] The controller can operate the first and second propulsion subsystems in parallel to drive the first and second vehicles concurrently. In one instance, the controller can operate the first and second propulsion subsystems independently of each other. For example, the controller can consider only information and data related to the first propulsion subsystem to drive the first shaft, without considering information from the second propulsion subsystem. In another instance, the controller operates the first and second propulsion subsystems together, such that information or data related to the first propulsion subsystem may cause dynamic modifications to the second propulsion subsystem.

[0058] In one example, the first energy storage device might have only enough charge remaining to effectively power the first engine for one hour, while the second energy storage device might have enough charge remaining to effectively power the second engine for three hours. Based on this information, the controller can reduce the discharge from the first energy storage device, resulting in lower efficiency for the first propulsion subsystem, while simultaneously increasing the discharge from the second energy storage device, resulting in higher efficiency for the second propulsion subsystem. Therefore, overall, the vehicle system can achieve the target efficiency of the journey without the first energy storage device losing all its charge.

[0059] During operation, as the vehicle system travels along a route during a journey, the control system can be configured to measure, record, or otherwise receive or collect input information about the route, the vehicle system, and the vehicle system's movement along the route. For example, the control system can be configured to monitor the vehicle system's position along the route and its speed along the route. Additionally, the control system can be configured to generate journey plans and / or control signals based on such information. The journey plans and / or control signals specify one or more operating settings for the vehicle system to be implemented or executed during the journey based on distance, time, and / or position along the route. Operating settings may include the vehicle system's traction and braking forces. For example, operating settings may indicate different speeds, throttle settings, braking settings, acceleration, etc., for the vehicle system at different locations, at different times, and / or along different distances of the route traversed by the vehicle system at different locations.

[0060] Trip planning can be configured to achieve or enhance specific purposes or objectives during the journey of a vehicle system, while satisfying or complying with specified constraints, limitations, and restrictions. Some possible objectives include improving energy efficiency (e.g., fuel and / or stored current), reducing emissions, shortening trip duration, increasing fine motor control, and reducing wheel and track wear. Constraints or restrictions include speed limits, timetables (such as arrival times at various specified locations), environmental regulations, standards, and restrictions on audible noise.

[0061] The trip plan's operating settings are configured to improve the achievement of specified objectives relative to the vehicle system traveling along the trip route, based on operating settings different from one or more operating settings in the trip plan (e.g., if the traction and braking settings for the trip are determined by the vehicle system's human operator). An example of a trip plan objective could be improving fuel and / or stored current efficiency by reducing fuel and / or energy consumption during the trip. By implementing the operating settings specified by the trip plan, fuel and / or energy consumption can be reduced relative to the same vehicle system traveling along the same segment of the route within the same time period, but without adhering to the trip plan.

[0062] Trip planning can be developed using algorithms based on a model of the vehicle system's behavior along a route. The algorithm can comprise a series of nonlinear differential equations derived from applicable physical equations through simplifying assumptions. The algorithm can also include the computations and algorithms described in this paper relating to hybrid-powered vehicles and utilizing energy storage devices to supplement the prime mover.

[0063] In one embodiment, the control system can be configured to generate multiple travel plans for a vehicle system to follow a route during the journey. The multiple travel plans may have different objectives than each other. The differences in objectives may be based on the operating conditions of the vehicle system. Operating conditions may be the vehicle system's fuel efficiency, the vehicle system's position along the route, etc. For example, in response to the vehicle system operating at an efficiency equal to and / or above a specified threshold efficiency, the vehicle system may move according to a first travel plan. In response to the vehicle system traveling at an efficiency below a specified threshold speed, the vehicle system may move according to a different second travel plan. Both the first and second travel plans may be generated by the control system before the vehicle system begins its journey. Alternatively, only the first travel plan may be generated before the journey, and the second travel plan may be generated during the vehicle system's journey in response to the vehicle system's operating conditions exceeding a specified threshold. For example, the second travel plan may be a modified or re-formulated travel plan that modifies or updates the previously generated first travel plan to account for the changing objectives.

[0064] In an alternative embodiment, instead of generating multiple different trip plans, the control system can be configured to generate a single trip plan that takes into account the changing objectives of the vehicle system along the route. For example, the trip plan can constructively divide the trip into multiple segments based on time, location, or the projected speed of the vehicle system along the route. In some segments, the trip plan's operating settings are specified to drive the vehicle system to achieve at least a first objective. In at least one other segment, the trip plan's operating settings are specified to drive the vehicle system to achieve at least a different second objective.

[0065] The control system can be configured to control the vehicle system along a journey based on a travel plan, causing the vehicle system to move according to the travel plan. In closed-loop mode or configuration, the control system can autonomously control or implement the propulsion and braking subsystems of the vehicle system according to the travel plan without human operator input. In open-loop calibration mode, the operator can participate in the control of the vehicle system according to the travel plan. For example, the control system can present or display the operating settings of the travel plan to the operator as guidance on how to control the vehicle system to follow the travel plan. The operator can then control the vehicle system in response to the guidance.

[0066] Figure 5 This is a flowchart of one embodiment of a method 500 for controlling a vehicle system that travels along one or more routes.

[0067] At point 502, one or more processors determine engine operating parameters. These parameters may include data, information, measurements, calculations, models, formulas, etc., that can be used to determine engine characteristics. These characteristics may include engine life, engine power, engine capacity, engine wear, engine usage, engine size, vehicle size, route, historical engine data under various weather conditions, route gradient, and engine performance data.

[0068] As an example, in one embodiment, a standard point mass representation can be considered in the embodiment of the vehicle system to calculate the traction power required for the journey, as provided below:

[0069] dvdt=F / mg(x)-a-bv-bv2

[0070] Where v is the velocity of the vehicle system, t is a function of time, F is the traction efficiency or traction force, m is the mass of the vehicle system, g(x) is the effective gradient of the journey, a and b are the Davis drag coefficients, and the trapezoidal discretization of the point mass model is:

[0071] h(Fk,Fk+1,αk,αk+1,δxk,a,b,c)=0

[0072] Where F is the traction efficiency or traction force, k is the index of the grid point, α is the reverse velocity, δxk is xk-xk-1, x is the distance along the journey and is the independent variable, and a, b, and c are the Davis drag coefficients. Vehicle characteristics can be a 1D lookup table or an engine fuel rate interpolated as a function of engine horsepower, as given below:

[0073] γk=Γ(Pek)

[0074] Where γ is the fuel combustion rate, k is the index of the grid point, and Pe is the engine power.

[0075] At point 504, one or more processors determine the operating parameters of the energy storage device. These operating parameters can include any data, information, measurements, calculations, models, formulas, etc., that can be used to determine the characteristics of the energy storage device. These characteristics can include battery capacity, battery C-rate, battery power, battery life, battery fuel savings; battery power limits, battery temperature, battery voltage, battery state of charge, battery depth of discharge, battery ohmic resistance, battery nameplate capacity, etc.

[0076] In one instance, a predictive battery life model can be used to determine battery life. In another instance, when the energy storage device can be used along one or more routes, battery life or energy storage device life can be modeled based on the vehicle's fuel consumption. The battery life model can calculate the aging associated with lithium-ion (Li-ion) batteries. The aging rate depends on the operating conditions described by temperature, voltage, and depth of discharge, as well as the number of battery cycles. Then, when the capacity has decayed by 20-30% of the rated capacity, the end of battery life can be determined. To address energy management issues, optimization-oriented approximations of the life model can be considered. Detailed models treat resistance growth (R) and capacity decay as aging mechanisms, where the increase in cell resistance due to calendar and cycle-driven mechanisms may be primarily additive, as provided below:

[0077] R = A0 + A1Δtlife0.5 + A2Δtlife

[0078] Where A is a parameter that can be fitted to a specific type of lithium battery based on battery cell test data, and Δtlife is the change in battery life. However, it is assumed that the battery capacity is controlled by the loss of cyclic lithium or the loss of active sites, as shown below:

[0079] QLi=B0-B1Δtlife0.5

[0080] Where QLi represents the loss of cyclic lithium, B is another parameter that can be fitted to a specific type of lithium battery based on cell test data, and Δtlife represents the change in battery life. Also used is:

[0081] Qsites=C0-C2Δtlife

[0082] Where Qsites represents the loss of active sites, C is a parameter that can be fitted to a specific type of lithium battery based on battery cell test data, and Δtlife is the change in battery life.

[0083] Typically, capacity degradation is more limiting than resistive growth. Furthermore, energy storage usage during the operation of a vehicle system will experience more cycle degradation than capacity degradation. Therefore, the aging rate is Qsites, where the aging factor C2 is given by:

[0084]

[0085] Where E a α c2β are fitting parameters. The default aging factor C2,ref is modulated by the reference value deviations of the voltage, temperature, and throughput terms. The throughput term is the cycle average of the depth of discharge, where the number of cycles Ncyci and the associated depth of discharge (DOD) are calculated over the entire battery life (Δtlife), which is sampled as a smaller fraction of battery operation Δtcyc.

[0086] Optimization-oriented models utilize these parameters and simplify the cyclic decay of aging, further enabling the design of tractable optimizers with approximations. As an example, from an optimization perspective, rainflow count analysis is unsuitable, and alternative representations can be considered. Instead of rainflow analysis for cycle counting, half a cycle is counted at each instant, and zero DOD will result in a zero throughput term if no battery power is consumed. In another instance, the travel time that can solve the power management problem typically occurs within several hours. Several hours is shorter than the sampling time assumed in parameter identification. Therefore, the reference aging rate is scaled and given by:

[0087] Kref = C2,ref(tf / Δtcyc)

[0088] Where Kref is the cyclic aging of tf under given battery operating and cycling conditions, C2,ref is the cyclic aging of Δtcyc under reference operating conditions, and Δtcyc is the sampling time for parameter identification of the lifetime model using battery cell test data.

[0089] In yet another instance, the discrete-time representation of optimizer-oriented aging (dQopt) is represented by the lifetime factor LF and is given by:

[0090]

[0091] Where N is the distance from grid points, E a It is the activation potential, and SOE is the battery temperature, voltage, and state of charge.

[0092] In another instance, the following approximation was considered:

[0093]

[0094] Where E a A and β are acceleration parameters for temperature, voltage, and throughput determined empirically.

[0095] In another example, a battery thermal and voltage model can be provided. Specifically, the heat generated due to battery use causes temperature variations, which affect battery life. Furthermore, reducing thermal fluctuations helps to reduce or minimize cooling requirements that are critical to battery temperature. The thermal model is provided by:

[0096]

[0097] Qent, representing the battery voltage's sensitivity to temperature, is a function of the battery's state of charge and is obtained from internal thermal testing. Based on testing and analysis, while Joule heat loss dominates at higher C-rates, entropy loss is significant at lower C-rates. The inlet airflow is assumed to be in the ambient environment, and a perfect cooling system is assumed. Thermal parameters Rbatt and Cbatt are identified internally through thermal module testing and analysis.

[0098]

[0099] By modeling the thermal properties of the energy storage device, the threshold operating temperature of the energy storage device can be determined. Furthermore, the voltage model is also a quadratic function of the SOE, where the fitting coefficients are determined based on cell test data.

[0100] Vk = f(SOEk2, SOEk)

[0101] At point 506, one or more processors generate a travel plan for the vehicle system's journey along the route based on at least one of the engine operating parameters or energy storage device operating parameters. The travel plan may be generated by a controller containing one or more processors. The travel plan specifies one or more operating settings that vary with one or more of the time or distance the vehicle system travels along the route. The operating settings are specified to drive the vehicle system to achieve one or more objectives in the travel plan.

[0102] The generated trip plan can include one or more of the following as the trip plan's operating settings: fuel efficiency, energy storage device usage, speed, throttle setting, braking setting, or acceleration. A trip plan can be generated to drive the vehicle system to achieve one or more objectives when one or more of the following are met: speed limits, vehicle capacity constraints, trip plan time, or emission limits.

[0103] In one instance, a look-ahead algorithm can be provided ( Figure 6 Furthermore, the prospective algorithm can be designed to leverage the battery to increase fuel savings while reducing battery aging, thereby justifying the fuel savings. The algorithm can consider user input as well as terrain and system configuration inputs. System configuration inputs can include engine operating parameters and battery operating parameters, as previously determined as described above.

[0104] For a given set of inputs, the algorithm enhances traction (Fk), speed (vk), and battery power (Pbk) over the entire journey duration, which reduces or minimizes a fuel life multi-objective function constrained by a set of constraints. The objective function is given as:

[0105]

[0106] Where ηtFkvk is the traction power, ηt is the traction efficiency, and Pnet(Pbk) is the net battery power available after considering battery system losses. The penalty parameter is considered to alter battery utilization to generate a trade-off curve, and is typically the ratio of battery to fuel cost. When battery costs are high, the parameter can be set to a higher value that limits battery usage to maintain lifespan, and vice versa. Therefore, the algorithm can be defined as follows:

[0107]

[0108] DOD is calculated as the change in SOE between consecutive time points (DODk = SOEk-3 SOEk-1). The reciprocal of the velocity (αk) is used because it helps to linearize many constraints, thus simplifying the problem.

[0109] The equations used in the algorithm represent the dynamics of the vehicle system, as well as battery state of charge and temperature. Additionally, travel time and speed limits may be described, along with traction and rate limits. Engine power can be calculated as the difference between the required traction power and the net battery power. Engine power can be limited as given, where Pmin and Pmax are engine limits. Total traction power may exceed the current upper limit of the throttle or notch value.

[0110] Constraints are also specific to battery utilization. These constraints include battery power temperature, SOE limits, and the rate of change of battery power. The lower and upper limits of battery power can be functions of SOE. For example, at a lower SOE, discharge capacity can be significantly reduced, thus limiting available power. Similarly, at a higher SOE, charging capacity can be significantly increased.

[0111] A tradeoff could be an engine-battery operation where fuel savings justify the cost of battery aging. In contrast, the algorithm for hybrid vehicles only reduces total fuel γ(ηtFkvk). Therefore, when λ >> 1, the solution approaches fuel optimality. The above algorithm can be classified as a nonlinear programming problem and can be solved using IpOpt, an interior-point solution. The scope of the described formulas can be limited to vehicle systems with independent power commands to the engine and battery. Furthermore, swarm configurations may be limited to conventional vehicle systems. The content of these options can be driven by vehicle system infrastructure such as high-voltage lines and swarm communication.

[0112] In yet another example, the travel plan may also include additional replenishment of the energy storage device along the route during the journey to provide additional power when traversing specific terrain. For example, the energy storage device may be electrically coupled to a local catenary that provides supplemental power to the energy storage device. Optionally, the energy storage device may be mechanically coupled to a roadside device such as a charging station during the journey. Optionally, the energy storage device may be electrically coupled to a current-carrying rail. In each case, the propulsion system receives supplemental power from a remote device coupled to the propulsion system.

[0113] Optionally, at 508, one or more processors determine the configuration of the vehicle system based on the determined operating parameters. As an example, when the vehicle can be a vehicle system comprising numerous propulsion and non-propulsion vehicles, the provided modeling and determinations can be used to determine how many hybrid vehicles should be provided in the vehicle system. In one instance, all propulsion vehicles in the vehicle system are hybrid vehicles, while in other instances, a combination of non-hybrid and hybrid vehicles is utilized. Additionally, the number of non-propulsion vehicles used in combination with hybrid vehicles needs to be determined. Therefore, in addition to the vehicle system's trip planning, the configuration of the vehicle itself can also be determined to improve efficiency, reduce battery aging, and lower costs.

[0114] Figure 6 This is a schematic diagram of one embodiment of a trip planning algorithm 600 according to one embodiment. The algorithm can receive input 602 from trip-related on-board and off-board sources, including vehicle-based input and trip-based input. The input can be received by a trip characterization element, a vehicle characterization element, one or more sensors, etc. In one example, as per [example missing] Figure 1 and Figure 2The described travel characterization elements, vehicle characterization elements, and one or more sensors can be inputs. Inputs may include vehicle configuration, route information, engine size, battery capacity, fuel cost, component replacement cost, etc. In one example, the vehicle may be a rail-based vehicle, which may include a combination of propulsed and non-propulsed vehicles. Propulsed vehicles may be driven by internal combustion engines, energy storage devices, hybrid vehicles, or combinations thereof. In one example, route information may include rail-related information, such as rail curvature information and rail traffic information.

[0115] The algorithm also receives constraints and limitations 604 associated with the vehicle system and the journey. For example, constraints and limitations may include journey travel time and speed limits, including speed limits in different regions of the journey. Constraints and limitations may also include traction and force factor limits. In one instance, traction and / or force factor limits are determined, such as in combination with... Figure 5 As described. Constraints and limitations may also include engine limitations, battery power, power limits, available SOE, thermal limitations, etc.

[0116] Based on inputs, constraints, and limitations, the algorithm can determine the energy management of a journey. In one instance, a penalty sweep curve can be provided by determining the lifetime factor of the energy storage device, compared to the amount of fuel saved by using an energy storage device. In another instance, such as combining... Figure 5 One or more of the described determinations and calculations can be used by the algorithm to make determinations. Therefore, output 606 is provided to the trip, which may include a trip plan. The output may include fuel savings compared to the energy storage device's lifespan penalty curve, traction power and speed during the trip, and may include various parts of the trip, battery power predictions during the trip, etc.

[0117] Figure 7A and 7B This demonstrates the fuel savings achieved by proportional life factor adjustment. Figure 7A ) and the proportional stroke detailed life model output proportional adjustment of fuel savings ( Figure 7B The graphs show the results of using a greedy algorithm compared to using a greedy algorithm. Figure 5 and Figure 6 A comparison of vehicle systems using the methods described in the paper. As shown, as the penalty for battery life increases (moving from right to left), battery utilization may decrease, resulting in fewer fuel savings. There is a trade-off between annual fuel savings and fuel savings over the duration of battery life. The same trend can be observed in… Figure 7B The diagram shows that the expected number of trips increases with the increase of the penalty. This is because as the penalty increases...

[0118] Figure 5 The method uses fewer batteries, and due to reduced aging, it may produce more similar trips.

[0119] Figure 8A and 8B A graph showing the distance traveled relative to the speed. Figure 8A ) and a graph of the distance traveled versus the proportion of fuel ( Figure 8B ). Figure 8A The terrain 802, or the hillside along the route, is also depicted. Each figure shows a comparison between the vehicle using the greedy algorithm 806 and the method described above. Figure 5 and Figure 6 A comparison of the vehicle system described in method 804. As shown, for a given aging or reduced aging, compared to the greedy algorithm, Figure 5 and Figure 6 This method saves more fuel. Therefore, reuse Figure 5 The method described in the paper improves fuel efficiency, thereby improving upon previous systems.

[0120] Figure 9A , 9B 9C and 9D demonstrate the distance of the stroke relative to the proportional engine power ( Figure 9A The graph of the distance traveled versus the proportional battery power. Figure 9B ); the graph of the distance traveled versus SOE ( Figure 9C ); and a graph showing the distance traveled versus the proportional battery temperature ( Figure 9D ), which can also display terrain 906. Each graph shows the difference between using a greedy algorithm 904 and using a different algorithm. Figure 5 and Figure 6 A comparison of the vehicle system described in method 902. As shown, for a given aging or reduced aging, compared to the greedy algorithm, Figure 5 The method is better implemented.

[0121] Figures 8A-8B The 9A-9F series demonstrates specific test cases to help understand... Figure 6 The algorithm and Figure 5 The method utilizes a fuel-saving mechanism. In this example, the terrain consists of uphill sections or uphill roads, followed by downhill sections or downhill roads. Figures 8A-8B A greedy approach and Figure 6 The algorithm compares the velocity and fuel predictions for two different initial SOEs. Similarly, Figures 9A-9DThe diagram shows the engine-battery power output, as well as the battery SOE and temperature. Because the greedy algorithm divides the total power from the optimal fuel solution into engine and battery power, it is consistent with... Figure 9E-9F The speed prediction is the same as that based on the greedy method in [the text].

[0122] Figure 6 The first advantage of this algorithm, which can save fuel better than the greedy method, is that... Figure 5 Methods and Figure 6 The algorithm incorporates complete trip information that can be used to provide the state of charge for the energy storage device, including when the battery is effectively charged / discharged. For a given travel time constraint, the algorithm uses battery power as much as possible to travel faster during uphill sections of the trip. This gain in travel time can then be offset by reducing engine power in these areas to travel slower during downhill sections, such as... Figure 8A As shown in the document. Figure 8B The fuel savings shown are a direct result of reduced engine power requirements.

[0123] Figure 6 Another advantage of the algorithm is that it can provide a dynamic boost that enables the modulation of speed based on terrain. Figures 8A-8B The diagram graphically represents the engine operating at its maximum power level, while the battery provides additional power to increase the vehicle's speed. However, battery utilization using a greedy algorithm can be complementary, not additional. This is because without predictive knowledge, it may be impossible to determine when and how much of the power boost can be offset. Certain parameters may need to be determined to maintain power until a specified travel time.

[0124] Figure 6 Another advantage of the algorithm is that, in addition to improving fuel savings, Figure 5 The proposed algorithm and method employ a variable C-rate within specified charging / discharging limits. Compared to a greedy algorithm, the use of a variable C-rate promotes less battery aging. The impact of the C-rate on battery life can be significant. Figure 9F Based on the temperature curves, the greedy algorithm method exhibits a wider temperature range compared to the proposed method. Furthermore, compared to existing methods, using an explicit battery model that considers thermal effects facilitates the determination of the C-rate based on heuristic methods.

[0125] like Figure 9E As demonstrated, the initial SOE's impact on fuel savings can be significant and applies to all methods. Therefore, Figure 5 and Figure 6 The relative fuel savings between the greedy approach and the method are 15% of the initial SOE at the low end and 90% of the initial SOE at the high end, such as Figure 9C As shown in the document.

[0126] use Figure 9C The SOE curves in the diagram provide a good understanding of the main differences between the proposed method and the greedy method. Figure 5 and Figure 6 The formula's approach considers charging the engine as an option when fuel savings are possible. For example, when the initial SOE is 15%, Figure 5 and Figure 6 The method uses this option, where the first charging event occurs at approximately distance = 10, so this energy can be used for sustained acceleration for a longer period. Sustained acceleration for a longer period saves fuel. This effect may be compromised when system architecture options increase track-to-traction losses.

[0127] The final aspect of the analysis could be validating average performance metrics. Optimal battery SOE and temperature profiles, such as... Figure 9E-9F As shown, the battery penalty A = [0.1, 1, 10, 100] is greedily added. Battery life is most sensitive to temperature, followed by voltage and throughput terms. For this reason, temperature changes, as well as average voltage and throughput terms, may be higher when the penalty on the battery can be minimized. When the penalty can be increased, Figure 6 The algorithm reduces battery aging. For this reason, the temperature can be kept relatively high, and the voltage value is low. In the case of the greedy algorithm, the higher C-rate reduces the average voltage while maintaining a higher temperature deviation. Therefore, another improvement to the greedy algorithm can be achieved.

[0128] Figure 10 A method 1000 for dynamically controlling the C-rate of a battery during a trip is presented. The battery C-rate is a measure of the rate at which a battery can be charged or discharged. In method 1000, the C-rate varies according to engine efficiency when trip planning is formulated. Method 1000 improves upon methods that maintain a constant C-rate when formulating trip plans, such as those using greedy algorithms.

[0129] At point 1002, one or more processors are configured to determine engine efficiency during the stroke. This can be discussed as described above. Figure 5The discussion focuses on determining engine efficiency. This involves determining the engine's operating parameters during the journey. Energy efficiency can be determined using operating parameters through lookup tables, algorithms as previously described, mathematical equations as previously described, etc. This includes the engine's efficiency on different terrains and along different sections of the journey. Specifically, when determining engine efficiency during the journey, the performance parameters of the engine and the energy storage device are determined based on the operating parameters. Engine performance parameters may include fuel efficiency, including miles per gallon, emissions produced by the engine during fuel combustion during the journey, engine temperature during the journey, etc. Meanwhile, energy storage device performance parameters may include discharge rate during the journey, storage capacity during the journey, etc. In some instances, the operating parameters of both the engine and the energy storage device can be used as separate performance parameters for the engine and the energy storage device, respectively.

[0130] At 1004, the one or more processors dynamically determine the battery's C-rate based on engine efficiency during the journey. Specifically, the battery's C-rate changes in response to changes in engine efficiency during the journey. Specifically, when engine efficiency increases, the C-rate decreases in response, and when engine efficiency decreases, the C-rate increases in response. For example, when a rail vehicle enters a densely populated area or a section of rail where the vehicle may need to slow down, the engine may operate at a lower notch, thus reducing engine efficiency. During this segment of the journey, when the vehicle speed decreases, resulting in a decrease in engine efficiency, the C-rate increases, thereby supplementing the engine and reducing its workload.

[0131] Similarly, when a vehicle leaves a densely populated area and may be able to increase speed, and position the notch in a more efficient location for the engine, the C-ratio decreases. Therefore, the engine operates with less supplementation when fuel is most efficient. In other instances, the C-ratio increases when the vehicle is ascending or going uphill, causing engine efficiency to decrease. When going downhill, engine efficiency increases, and the C-ratio may decrease. Improved operation can be achieved by adjusting the C-ratio based on engine efficiency. To determine engine efficiency and the C-ratio, the one or more processors may use algorithms, mathematical equations, lookup tables, etc.

[0132] At 1006, the one or more processors modify the battery output in response to the C-rate. In one instance, the battery output may decrease in response to a determined increase in engine efficiency during the trip. Alternatively, in another instance, the battery output may increase in response to a decrease in engine efficiency. Specifically, the one or more processors may provide instantaneous charging commands to charge or discharge the battery based on the engine efficiency during the trip. Alternatively, additional factors, including the terrain of the route during the trip, may be used to determine when to charge and discharge the battery. Although Figure 10 The method is described in relation to a single propulsion vehicle, but the system can provide many propulsion vehicles, such as those relative to... Figure 1 What is shown.

[0133] In yet another example, the controller may incorporate artificial intelligence that uses algorithms to determine the most efficient way to use the first and second batteries when replenishing the first and second engines along a given route. Based on the experience of other vehicles and / or the first and second vehicles, charging commands that result in the most efficient operation of the vehicle system on a given route are weighted. Therefore, when the vehicle system is again on the same route, the most efficient use of the first and second batteries is determined. In this way, the controller becomes more effective in achieving the objectives of the trip plan as more data related to a given vehicle route can be learned.

[0134] In one or more embodiments, a method may be provided, the method comprising: obtaining an operating configuration specified for moving a first vehicle system along one or more routes during a journey to drive the first vehicle system to achieve one or more objectives; and determining operating parameters of an engine and an energy storage device. The method may further comprise: determining engine usage during the journey based on the engine operating parameters, the energy storage device operating parameters, and the one or more objectives; and determining energy storage device usage during the journey based on the engine operating parameters, the energy storage device operating parameters, and the one or more objectives, including when the energy storage device is charged or discharged during the journey.

[0135] Optionally, the operating parameters of the energy storage device are determined based on the predicted lifespan of the energy storage device. Alternatively, when the energy storage device is used along one or more routes, the predicted lifespan of the energy storage device is determined based on fuel consumption.

[0136] Optionally, the operating parameters of the energy storage device are based on the thermal properties of the energy storage device, and a threshold operating temperature of the energy storage device is determined based on the thermal properties. In one example, the operating parameters of the energy storage device may include at least two of the following: battery capacity, battery C-rate, battery power, battery aging, battery life, battery fuel consumption; battery power limit, battery temperature, battery voltage, battery state of charge, battery depth of discharge, battery ohmic resistance, or battery nameplate capacity.

[0137] Optionally, the method may further include modifying the usage of the energy storage device based on the terrain of the one or more routes. Alternatively, the usage of the energy storage device can be modified based on the terrain of the one or more routes by increasing the usage of the energy storage device when the vehicle traverses an uphill section of the terrain and charging the energy storage device when the vehicle traverses a downhill section of the terrain. In one example, the method may further include increasing the usage of the energy storage device when the vehicle traverses an uphill section of the terrain.

[0138] Optionally, the trip plan may include charging the energy storage device during the trip using an electric current from at least one of the following: the engine, the engine of the second vehicle, the braking system of the vehicle, or the braking system of the second vehicle. Alternatively, the trip plan may be generated by determining one or more of the times or locations during the trip where the vehicle system is stopped to charge the energy storage device.

[0139] Optionally, the trip plan can be generated by specifying one or more of the following as the operating settings of the trip plan: the charging state of the energy storage device, the setting of the energy storage device, the speed of the vehicle system, the throttle setting of the vehicle system, the braking setting of the vehicle system, or the acceleration of the vehicle system.

[0140] In one or more embodiments, a system may be provided that includes a controller configured to specify one or more operating settings for a vehicle at different locations, at different times, or at different distances along one or more routes. These operating settings are specified to drive the vehicle to achieve one or more objectives during the journey by controlling the use of the vehicle's engine and energy storage device during the journey. Both the engine and the energy storage device can operate to propel the vehicle during the journey. The engine's use during the journey may be based on engine operating parameters, energy storage device operating parameters, and the one or more objectives, and the energy storage device's use during the journey may be based on the engine operating parameters, energy storage device operating parameters, and the one or more objectives, including when the energy storage device is charged or discharged during the journey.

[0141] Optionally, the vehicle may be a first vehicle in a vehicle system, which may also include a second vehicle. Alternatively, the controller may be configured to specify one or more operating settings for the second vehicle at different locations, times, or distances along one or more routes to drive the second vehicle to achieve one or more target journeys during the trip by controlling the use of the second vehicle's second engine and second energy storage device. In one example, the controller may be configured to specify one or more operating settings for the first vehicle independently of specifying the one or more operating settings for the second vehicle.

[0142] Optionally, the controller may be configured to determine at least two of the following for the energy storage device: battery capacity, battery C-rate, battery power, battery aging, battery life, battery fuel savings, battery power limit, battery temperature, battery voltage, battery state of charge, battery depth of discharge, battery ohmic resistance, or battery nameplate capacity. In another example, the controller may be configured to control the operation of the vehicle to maintain the temperature of the energy storage device below a threshold temperature.

[0143] In one or more embodiments, a method may be provided that includes obtaining specified operating settings for moving a vehicle system along one or more routes during a journey to drive the vehicle system to achieve one or more objectives. The method may include: determining engine performance parameters and energy storage device performance parameters based on the obtained operating settings; determining the efficiency of the engine during the journey based on the engine performance parameters, the energy storage device performance parameters, and the one or more objectives; and determining the usage of the energy storage device during the journey based on the engine performance parameters, the energy storage device performance parameters, and the one or more objectives, including when to charge or discharge the energy storage device during the journey. The usage of the energy storage device may include changing the C-rate of the vehicle's battery based on the engine performance parameters and the energy storage device performance parameters.

[0144] Optionally, changing the C-rate may include reducing the battery output in response to an increase in the engine's efficiency. Alternatively, changing the C-rate may include increasing the battery output in response to a decrease in the engine's efficiency.

[0145] As used herein, the terms “processor” and “computer,” as well as related terms such as “processing device,” “computing device,” and “controller,” are not limited to those integrated circuits referred to in the art as computers, but refer to microcontrollers, microcomputers, programmable logic controllers (PLCs), field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), and other programmable circuits. Suitable memory may comprise, for example, computer-readable media. Computer-readable media may be, for example, random access memory (RAM), computer-readable non-volatile media such as flash memory, etc. The term “non-transitory computer-readable media” means a tangible computer-based device implemented for short-term and long-term storage of information such as computer-readable instructions, data structures, program modules and submodules, or other data in any device. Thus, the methods described herein can be encoded as executable instructions embodied in a tangible non-transitory computer-readable medium, which includes, but is not limited to, storage devices and / or memory devices. Such instructions, when executed by a processor, cause the processor to perform at least a portion of the methods described herein. Thus, the term includes tangible computer-readable media, including but not limited to non-transitory computer storage devices, including but not limited to volatile and non-volatile media, and removable and non-removable media such as firmware, physical and virtual storage devices, CD-ROMs, DVDs, and other digital sources such as networks or the Internet.

[0146] Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “the” include plural indicators. “Optional” or “optionally” means that the event or situation subsequently described may or may not occur, and the description may include instances where the event occurred and instances where the event did not occur. Approximate language as used herein throughout the specification and claims may be used to modify any quantitative expression that may be permitted to vary without causing a change in the essential function that may be associated with it. Therefore, values ​​modified by one or more terms such as “about,” “substantially,” and “approximately” may not be limited to the specified precise value. In at least some cases, approximate language may correspond to the precision of the instrument used to measure the value. Scope limitations may be combined and / or interchanged herein and throughout the specification and claims, and such scope may be definite and include all subscopes contained therein, unless the context or language indicates otherwise.

[0147] This written description uses examples to disclose embodiments containing the best mode and to enable those skilled in the art to practice the embodiments, including making and using any apparatus or system and performing any incorporated methods. The claims define the patentable scope of this disclosure and include other examples that may occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that are not different from the literal language of the claims, or if they include equivalent structural elements that are not substantially different from the literal language of the claims.

Claims

1. A method for controlling the movement of a vehicle system, characterized in that, The method includes: Obtain input from at least one sensor; The controller generates operating settings based on the input to enable the first vehicle system to move along one or more routes during the journey, thereby driving the first vehicle system to achieve one or more objectives; Engine operating parameters and energy storage device operating parameters are determined, the energy storage device operating parameters being determined based on predicted energy storage device degradation during the trip calculated using a predicted battery life model of the energy storage device, wherein the predicted battery life model is configured to calculate the predicted energy storage device degradation during the trip based on the operating conditions of the energy storage device during the trip; The engine usage during the journey is determined based on the engine operating parameters, the energy storage device operating parameters, and the one or more targets. Based on the engine operating parameters, the energy storage device operating parameters, and the one or more targets, determine the usage of the energy storage device during the trip, including when to charge or discharge the energy storage device during the trip; and Based on the engine usage and energy storage device usage during the journey, the first vehicle system moves along one or more routes.

2. The method according to claim 1, characterized in that, The predicted battery life model is configured to calculate the predicted energy storage device degradation during the trip based on fuel consumption when the energy storage device is used along one or more routes.

3. The method according to claim 1, characterized in that, The operating parameters of the energy storage device are based on the thermal properties of the energy storage device, and the threshold operating temperature of the energy storage device is determined based on the thermal properties.

4. The method according to claim 1, characterized in that, The operating parameters of the energy storage device include at least two of the following: battery capacity, battery C-rate, battery power, battery aging, battery life, battery power limit, battery temperature, battery voltage, battery state of charge, battery depth of discharge, battery ohmic resistance, or battery nameplate capacity.

5. The method according to claim 1, characterized in that, The method further includes: The usage of the energy storage device is modified based on the terrain of one or more routes.

6. The method according to claim 5, characterized in that, The usage of the energy storage device is modified based on the terrain of one or more routes by increasing the usage of the energy storage device when the first vehicle system traverses the uphill section of the terrain and charging the energy storage device when the first vehicle system traverses the downhill section of the terrain.

7. The method according to claim 6, characterized in that, The method further includes: When the first vehicle system traverses the uphill section of the terrain, the use of the energy storage device is increased.

8. The method according to claim 1, characterized in that, The method includes: A trip plan is generated based on the usage of the engine during the trip and the usage of the energy storage device during the trip; and the trip plan includes charging the energy storage device during the trip using a current from at least one of: the engine of the first vehicle system, the engine of the second vehicle system, the braking system of the first vehicle system, or the braking system of the second vehicle system.

9. The method according to claim 1, characterized in that, The method includes: A trip plan is generated based on the engine's usage during the trip and the energy storage device's usage during the trip; and wherein the trip plan is generated by determining one or more of the time or location during the trip when the first vehicle system is stopped to charge the energy storage device.

10. The method according to claim 1, characterized in that, The method includes: A trip plan is generated based on the engine's usage during the trip and the energy storage device's usage during the trip; and wherein the trip plan is generated by specifying one or more of the following as the operating settings of the trip plan: the charging state of the energy storage device, the setting of the energy storage device, the speed of the first vehicle system, the throttle setting of the first vehicle system, the braking setting of the first vehicle system, or the acceleration of the first vehicle system.

11. A vehicle control system, characterized in that, The system includes: A controller configured to specify one or more operating settings for a vehicle at different locations, at different times, or at different distances along one or more routes, the one or more operating settings being specified to drive the vehicle to achieve one or more objectives during the journey by controlling the use of the vehicle's engine and energy storage devices during the journey; The engine and the energy storage device operate to propel the vehicle during the journey; The engine usage during the journey is based on engine operating parameters, energy storage device operating parameters, and one or more objectives; The usage of the energy storage device during the trip is based on the engine operating parameters, the energy storage device operating parameters, and one or more objectives, including when to charge or discharge the energy storage device during the trip; The operating parameters of the energy storage device are determined based on the predicted energy storage device degradation during the trip, calculated using a predicted battery life model of the energy storage device. The predicted battery life model is configured to calculate the predicted energy storage device degradation during the trip based on the operating conditions of the energy storage device during the trip. The controller is configured to specify one or more operating settings for the vehicle based on the operating parameters of the energy storage device to drive the vehicle.

12. The system according to claim 11, characterized in that, The vehicle is the first vehicle in a vehicle system, which also includes a second vehicle.

13. The system according to claim 12, characterized in that, The controller is configured to specify one or more operating settings for the second vehicle at different locations, at different times, or at different distances along one or more of the one or more routes, in order to drive the second vehicle to achieve one or more objectives during the journey by controlling the use of the second engine and the second energy storage device of the second vehicle.

14. The system according to claim 13, characterized in that, The controller is configured to specify the one or more operating settings of the first vehicle independently of the one or more operating settings specified for the second vehicle.

15. The system according to claim 11, characterized in that, The controller is configured to determine at least two of the following for the energy storage device: battery capacity, battery C-rate, battery power, battery aging, battery life, battery power limit, battery temperature, battery voltage, battery state of charge, battery depth of discharge, battery ohmic resistance, or battery nameplate capacity.

16. The system according to claim 11, characterized in that, The controller is configured to control the operation of the vehicle to maintain the temperature of the energy storage device below a threshold temperature.

17. A method for determining the usage status of an energy storage device, characterized in that, The method includes: Obtain a specified operating setup for causing the vehicle system to move along one or more routes during a journey, in order to drive the vehicle system to achieve one or more objectives; Based on the obtained operating settings, determine the performance parameters of the engine and the energy storage device. The efficiency of the engine during the journey is determined based on the engine's performance parameters, the energy storage device's performance parameters, and the one or more objectives. Based on the engine's performance parameters, the energy storage device's performance parameters, and the one or more targets, determine the use of the energy storage device during the journey, including when to charge or discharge the energy storage device during the journey; The use of the energy storage device includes changing the C-rate of the vehicle's battery based on the performance parameters of the engine and the performance parameters of the energy storage device.

18. The method according to claim 17, characterized in that, Changing the C-multiplier includes: The output of the energy storage device is reduced in response to the increase in the efficiency of the engine.

19. The method according to claim 17, characterized in that, Changing the C-multiplier includes: The output of the energy storage device is increased in response to the decrease in the efficiency of the engine.

Images