System and method for efficient driving

Abstract

A method of optimizing energy consumption includes receiving vehicle route information, generating a reference vehicle route profile including a reference energy consumption and a reference travel time, and processing the reference vehicle route profile by detecting one or more changes in road grade. For each detected change in road grade, the method includes triggering a breakpoint to divide the reference vehicle route profile into a plurality of segments, each of the plurality of segments having a reference vehicle speed, and for each of the plurality of segments, performing a local optimization to generate a modified vehicle speed. The method also includes generating an updated vehicle route profile and performing a global optimization on the updated vehicle route profile to generate an optimized vehicle route profile, the optimized vehicle route profile having a different energy consumption than the reference energy consumption.

Description

Technical Field

[0001] The present invention generally relates to optimizing the energy consumption of a vehicle. In both fossil fuel and electric vehicles, aerodynamic losses affect the energy consumption of the vehicle. Typically, during a driving route, vehicle speed and headwind speed have the greatest impact on aerodynamic losses, wherein vehicle speed can be manipulated or adjusted to optimize energy consumption while balancing the travel time of the driving route. Background Art

[0002] The information provided in this section is for the purpose of generally presenting the background of the present disclosure. To the extent described in this section, the work of the presently named inventors, as well as aspects of the description that may not qualify as prior art at the time of filing, are neither explicitly nor implicitly admitted to be prior art with respect to the present disclosure. Summary of the invention

[0003] In one configuration, a system and method include receiving vehicle route information, generating a baseline vehicle route profile, the baseline vehicle route profile including engine torque and engine speed, generating a baseline energy consumption and a baseline travel time for the baseline vehicle route profile based on the engine torque and engine speed of the baseline vehicle route profile, and processing the baseline vehicle route profile by detecting one or more changes in a road grade of the baseline vehicle route profile. For each detected change in the road grade of the baseline vehicle route profile, the system and method triggers a breakpoint to divide the baseline vehicle route profile into a plurality of segments, each corresponding segment in the plurality of segments having a baseline vehicle speed. For each corresponding segment in the plurality of segments of the baseline vehicle route profile, the system and method performs a local optimization to generate a revised vehicle speed, and generates an updated vehicle route profile based on the revised vehicle speed for each segment in the plurality of segments. Finally, the system and method performs a global optimization on the updated vehicle route profile to generate an optimized vehicle route profile, the optimized vehicle route profile having an optimized energy consumption different from the baseline energy consumption of the baseline vehicle route profile.

[0004] The system and method may include one or more of the following optional features. For example, the operation may further include providing an optimized vehicle route profile to a vehicle controller. The vehicle route information may include at least one of route map data, route slope data, vehicle headwind speed, or vehicle local data. The vehicle local data may include at least one of vehicle mass, powertrain data, vehicle transmission gear ratio, or vehicle aerodynamic coefficient.

[0005] In one configuration, performing local optimization to generate a revised vehicle speed may include receiving external route data, determining that the road slope is negative, and increasing the baseline vehicle speed based on the variance factor and the external route data. The external route data may include at least one of headwind speed, traffic congestion, or traffic signal information. Additionally or alternatively, performing local optimization to generate a revised vehicle speed may include receiving external route data, determining that the road slope is positive, and decreasing the baseline vehicle speed based on the variance factor and the external route data. The external route data may include at least one of headwind speed, traffic congestion, or traffic signal information.

[0006] The operations may also include determining that a difference between an optimized travel time and a benchmark travel time for the optimized vehicle route profile exceeds an acceptability threshold, and generating a user-selectable option for output to the driver that, when selected, authorizes the optimized vehicle route profile. The user-selectable option may be provided as an output of a vehicle user interface.

[0007] In another configuration, a system and method may include data processing hardware and memory hardware in communication with the data processing hardware, the memory hardware storing instructions that, when executed on the data processing hardware, cause the data processing hardware to perform operations including: receiving vehicle route information, generating a baseline vehicle route profile, the baseline vehicle route profile including engine torque and engine speed, generating a baseline energy consumption and a baseline travel time for the baseline vehicle route profile based on the engine torque and engine speed of the baseline vehicle route profile, and processing the baseline vehicle route profile by detecting one or more changes in a road grade of the baseline vehicle route profile. For each detected change in the road grade of the baseline vehicle route profile, the system and method triggers a breakpoint to divide the baseline vehicle route profile into a plurality of segments, each corresponding segment in the plurality of segments having a baseline vehicle speed. For each corresponding segment in the plurality of segments of the baseline vehicle route profile, the system and method performs a local optimization to generate a revised vehicle speed. The system and method generates an updated vehicle route profile based on the revised vehicle speed of each segment in the plurality of segments. Finally, the system and method performs a global optimization on the updated vehicle route profile to generate an optimized vehicle route profile having an optimized energy consumption that is different from a baseline energy consumption of the baseline vehicle route profile.

[0008] The system and method may include one or more of the following optional features. For example, the operation may further include providing an optimized vehicle route profile to a vehicle controller. The vehicle route information may include at least one of route map data, route slope data, vehicle headwind speed, or vehicle local data. The vehicle local data may include at least one of vehicle mass, powertrain data, vehicle transmission gear ratio, or vehicle aerodynamic coefficient.

[0009] In one configuration, performing local optimization to generate a revised vehicle speed may include receiving external route data, determining that the road grade is negative, and increasing the base vehicle speed based on a variance factor and the external route data. The external route data may include at least one of headwind speed, traffic congestion, or traffic signal information. Performing local optimization to generate a revised vehicle speed may include receiving external route data, determining that the road grade is positive, and decreasing the base vehicle speed based on the variance factor and the external route data.

[0010] The external route data may include at least one of headwind speed, traffic congestion, or traffic signal information. The operations may also include determining that a difference between an optimized travel time and a benchmark travel time for the optimized vehicle route profile exceeds an acceptability threshold, and generating a user selectable option for output to the driver that, when selected, authorizes the optimized vehicle route profile. The user selectable option may be provided as an output of a vehicle user interface. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The drawings described herein are for illustrative purposes only of selected configurations and are not intended to limit the scope of the present disclosure.

[0012] Figure 1A and 1B is a schematic diagram of an example system including an energy conservation system according to the principles of the present disclosure;

[0013] Figure 2 yes Figure 1A and 1B A schematic diagram of example components of an energy saving system;

[0014] Figure 3 is a schematic diagram of a vehicle route map including changes in road grade; and

[0015] Figure 4 is a flow chart of an example operational arrangement of a method for optimizing vehicle energy consumption.

[0016] Corresponding reference characters indicate corresponding parts throughout the several views. DETAILED DESCRIPTION

[0017] Example configurations will now be described more fully with reference to the accompanying drawings. Example configurations are provided so that the present disclosure will be thorough and will fully convey the scope of the present disclosure to those of ordinary skill in the art. Specific details, such as examples of specific components, devices, and methods, are set forth to provide a thorough understanding of the configurations of the present disclosure. It will be apparent to those of ordinary skill in the art that specific details need not be employed, that example configurations may be implemented in many different forms, and that the specific details and exemplary configurations should not be construed as limiting the scope of the present disclosure.

[0018] The terms used herein are only for describing specific exemplary configurations, not for limiting. As used herein, the singular articles "a", "an" and "the" may also be intended to include plural forms, unless the context clearly indicates otherwise. The terms "comprise", "include", "contain" and "have" are inclusive, thus specifying the presence of features, steps, operations, elements and / or parts, but do not exclude the presence or addition of one or more other features, steps, operations, elements, parts and / or groups thereof. The method steps, processes and operations described herein should not be interpreted as necessarily requiring them to be performed in the specific order discussed or shown, unless specifically identified as an execution order. Additional or alternative steps may be adopted.

[0019] When an element or layer is referred to as being "on another element or layer," "engaged to," "connected to," "attached to," or "coupled to" another element or layer, it may be directly on, engaged, connected, attached to, or coupled to another element or layer, or there may be intermediate elements or layers. Conversely, when an element is referred to as being "directly on another element or layer," "directly engaged to," "directly connected to," "directly attached to," or "directly coupled to" another element or layer, there may be no intermediate elements or layers. Other words used to describe the relationship between elements should be interpreted in a similar manner (e.g., "between" versus "directly between," "adjacent" versus "directly adjacent," etc.). As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0020] The terms first, second, third, etc. can be used here to describe various elements, components, regions, layers and / or parts. These elements, components, regions, layers and / or parts should not be limited by these terms. These terms are only used to distinguish each element, component, region, layer or part. Terms such as "first", "second" and other numerical terms do not imply order or sequence unless the context clearly indicates. Therefore, the first element, component, region, layer or part discussed below can be referred to as the second element, component, region, layer or part, without departing from the teaching of the example configuration.

[0021] In this application, including the definitions below, the term module may be replaced by the term circuit. The term "module" may refer to or be part of an application specific integrated circuit (ASIC), or include an application specific integrated circuit (ASIC); a digital, analog, or mixed analog / digital discrete circuit; a digital, analog, or mixed analog / digital integrated circuit; a combinational logic circuit; a field programmable gate array (FPGA); a processor (shared, dedicated, or group) that executes code; a memory (shared, dedicated, or group) that stores code executed by the processor; other suitable hardware components that provide the functionality; or a combination of some or all of the above, such as in a system on a chip.

[0022] The term code used above may include software, firmware and / or microcode, and may refer to a program, a routine, a function, a class and / or an object. The term shared processor includes a single processor that executes some or all of the code from multiple modules. The term group processor includes a processor that executes some or all of the code from one or more modules in combination with an additional processor. The term shared memory includes a single memory that stores some or all of the code from multiple modules. The term group memory includes a memory that stores some or all of the code from one or more modules in combination with an additional memory. The term memory may be a subset of the term computer-readable medium. The term computer-readable medium does not include transient electrical signals and electromagnetic signals propagated through the medium and can therefore be considered to be tangible non-transitory memory. Non-limiting examples of non-transitory memory include tangible computer-readable media, including non-volatile memory, magnetic memory, and optical memory.

[0023] The apparatus and methods described in this application may be implemented in part or in whole by one or more computer programs executed by one or more processors. The computer program includes processor executable instructions stored on at least one non-transitory tangible computer readable medium. The computer program may also include and / or rely on stored data.

[0024] Software applications (i.e., software resources) may refer to computer software that enables a computing device to perform tasks. In some examples, software applications may be referred to as "applications," "apps," or "programs." Example applications include, but are not limited to, system diagnostic applications, system management applications, system maintenance applications, word processing applications, spreadsheet applications, messaging applications, media streaming applications, social networking applications, and gaming applications.

[0025] Non-transitory memory can be a physical device used to temporarily or permanently store programs (e.g., instruction sequences) or data (e.g., program state information) for use by a computing device. Non-transitory memory can be volatile and / or non-volatile addressable semiconductor memory. Examples of non-volatile memory include, but are not limited to, flash memory and read-only memory (ROM) / programmable read-only memory (PROM) / erasable programmable read-only memory (EPROM) / electrically erasable programmable read-only memory (EEPROM) (e.g., commonly used for firmware, such as bootloaders). Examples of volatile memory include, but are not limited to, random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), phase change memory (PCM), and disk or tape.

[0026] These computer programs (also referred to as programs, software, software applications, or code) include machine instructions for a programmable processor and may be implemented in high-level procedural and / or object-oriented programming languages ​​and / or assembly / machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, non-transitory computer-readable medium, apparatus, and / or device (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0027] Various implementations of the systems and techniques described herein can be realized in digital electronic and / or optical circuits, integrated circuits, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs executable and / or interpretable on a programmable system comprising at least one programmable processor, which may be special purpose or general purpose, coupled to receive data and instructions from a storage system, and to send data and instructions to the storage system.

[0028] The processes and logic flows described in this specification can be performed by one or more programmable processors, also known as data processing hardware, executing one or more computer programs to perform functions by operating on input data and generating outputs. These processes and logic flows can also be performed by dedicated logic circuits, such as FPGAs (field programmable gate arrays) or ASICs (application-specific integrated circuits). For example, processors suitable for executing computer programs include general-purpose and special-purpose microprocessors, and any one or more processors of any kind of digital computer. Typically, the processor will receive instructions and data from a read-only memory or a random access memory or both. The basic elements of a computer are a processor for executing instructions and one or more storage devices for storing instructions and data. Typically, a computer will also include or be operably connected to one or more large-capacity storage devices for storing data, such as magnetic disks, magneto-optical disks, or optical disks, to receive data from the large-capacity storage device or to transmit data to it, or both. However, a computer does not need to have such a device. Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media and storage devices, including, for example, semiconductor memory devices, such as EPROM, EEPROM and flash memory devices; magnetic disks, such as internal hard disks or removable disks; magneto-optical disks; and CD ROM and DVD-ROM disks. The processor and memory may be supplemented by or incorporated in special purpose logic circuitry.

[0029] To provide interaction with a user, one or more aspects of the present disclosure may be implemented on a computer having a display device for displaying information to the user, such as a CRT (cathode ray tube), LCD (liquid crystal display) monitor, or touch screen, and an optional keyboard and pointing device, such as a mouse or trackball, through which the user can provide input to the computer. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback, such as visual feedback, auditory feedback, or tactile feedback; and input from the user may be received in any form, including sound, voice, or tactile input. In addition, the computer may interact with the user by sending documents to and receiving documents from a device used by the user; for example, by sending a web page to a web browser on a user's client device in response to a request received from the web browser.

[0030] Figure 1A and 1BAn example system 100a, 100b is shown including a vehicle 10 and / or a remote system 60 that communicates with the vehicle 10 via a network 40. The vehicle 10 and / or the remote system 60 executes an energy saving system 200, which a user can use when planning a vehicle route to generate an optimized vehicle route that saves energy consumption of the vehicle 10. In the example shown, the energy saving system 200 is implemented within the vehicle 10. However, the energy saving system 200 can be implemented on other computing devices (e.g., computing devices that communicate with the vehicle 10), such as, but not limited to, smart phones, tablets, smart displays, desktops / laptops, smart watches, smart appliances, headphones, smart glasses / headsets, or vehicle infotainment devices. The vehicle 10 includes data processing hardware 12 and memory hardware 14 that stores instructions that, when executed on the data processing hardware 12, cause the data processing hardware 14 to perform operations. The remote system 60 (e.g., a server, a cloud computing environment) also includes data processing hardware 62 and memory hardware 64 storing instructions that, when executed on the data processing hardware 62, cause the data processing hardware 62 to perform operations. In some examples, the execution of the energy saving system 200 is shared by the vehicle 10 and the remote system 60. As described below with reference to Figure 2 In more detail, the energy conservation system 200 executed on the vehicle 10 and / or the remote system 60 executes a vehicle and route grade module 210, a route grade processor 220, a local optimization module 230, an energy consumption module 240, and a global optimization module 250. The energy conservation system 200 is configured to receive vehicle route information 202 of the vehicle 10 and generate an optimized vehicle route profile 252 that conserves energy of the vehicle 10 while limiting delays in the travel time of the vehicle 10.

[0031] The vehicle route information 202 may include at least one of route mapping data, vehicle headwind speed, or vehicle local data, and may be stored on the vehicle 10 (e.g., memory hardware 14) or may be received from a remote system 60. The vehicle 10 may receive the vehicle route information 202 in response to the driver of the vehicle 10 initiating a new planned route, or the vehicle 10 may receive the vehicle route information 202 without human interaction (e.g., for an autonomous route). The route mapping data may include, but is not limited to, the vehicle route, the indicated speed of the vehicle route, and the road grade data of the vehicle route. The vehicle local data may include, but is not limited to, vehicle payload, vehicle powertrain map (e.g., brake specific consumption, torque curve, etc.), battery specifications, motor specifications, transmission gear ratios, and aerodynamic coefficients.

[0032] refer to Figure 1A and Figure 2, the vehicle 10 executes an energy conservation system 200 that receives vehicle route information 202 as input and generates an optimized vehicle route profile 252 as output. The energy conservation system 200 also includes a vehicle and route gradient module 210, a route gradient processor 220, a local optimization module 230, an energy consumption module 240, and a global optimization module 250. The vehicle route gradient module 210 is configured to receive the vehicle route information 202 and generate a baseline vehicle route profile 212. The vehicle route profile 212 may include the engine torque T at any given time along the vehicle route profile 212. e 214. Engine speed ω e 216 and road grade 218. The engine torque T at any given time along the vehicle route profile 212 e 214 can be represented as follows:

[0033]

[0034] Where R is the wheel radius of the vehicle, m eff represents the mass of the vehicle 10, the inertia moment J of the rotating element of the vehicle 10 and the wheel radius, g represents the gravity constant, γ represents the rolling resistance coefficient of the vehicle, φ represents the road slope 218, v w represents the headwind speed, v represents the vehicle speed, represents the air density at 25°C, A represents the front area of ​​the vehicle 10, C d represents the air resistance coefficient of the vehicle 10, η can be expressed as follows:

[0035] η=G r *FD (2)

[0036] Among them, G r denotes a gear ratio of the vehicle 10 , and FD denotes a final drive ratio of the vehicle 10 .

[0037] The engine speed ω at any given time along the vehicle route profile 212 e 216 can be represented as follows:

[0038] ω e =η.[ω tire ] (3)

[0039] Among them, ω tire Indicates the wheel speed of the vehicle 10 .

[0040] Once the engine torque T e 214 and engine speed ω e 216 is generated as an output from the vehicle speed and route grade module 210 , the energy consumption model 240 may receive the engine torque T e 214 and engine speed ωe 216 as input and generates as output a baseline energy consumption 242 and a baseline travel time 244 for the baseline vehicle route profile 212. In other words, the energy consumption model 240 can determine the amount of energy and time that a vehicle route will require without any optimization.

[0041] In addition, the route gradient processor 220 may receive as input the baseline vehicle route profile 212 including the road gradient 218 along the baseline vehicle route profile 212 and generate as output a plurality of segments 304, 304a-n of the baseline vehicle route profile 212. Specifically, the route gradient processor 220 processes the baseline vehicle route profile 212 by detecting one or more changes in the road gradient 218. The change may be any change (e.g., positive, negative) in the road gradient along the baseline vehicle route profile 212. For each detected change in the road gradient 218 of the baseline vehicle route profile 212, the route gradient processor 220 triggers the breakpoints 302 to divide the baseline vehicle route profile 212 into the plurality of segments 304. In other words, each segment 304 includes a single road gradient 218.

[0042] Each respective segment 304 in the plurality of segments 304 may include a baseline vehicle speed ω corresponding to the baseline vehicle route profile 212 veh 306, 306a-n. For example, refer to Figure 3 , schematic diagram 300 shows a road gradient 218 of a baseline vehicle route profile 212 disposed on an x-axis representing the vehicle route and a y-axis representing the road gradient. Here, the route gradient processor 220 detects a plurality of changes in the road gradient 218 and triggers a breakpoint 302 to segment / divide the baseline vehicle route profile 212. As shown, the route gradient processor 220 breakpoint 302 generates the baseline vehicle profile 212 into segments 304a-304g, wherein each of the segments 304a-304g includes a corresponding vehicle speed ω veh 306-306g.

[0043] Reference again Figure 1A and Figure 2 The local optimization module 230 receives the corresponding vehicle speed ω veh 306, and for each respective segment 304 in the plurality of segments 304, performing a local optimization to generate a modified vehicle speed ω veh_new 232. Specifically, the local optimization module 230 uses the road grade 218 for each respective segment 304 and applies a variation factor (e.g., a 10% increase or a 10% decrease) based on whether the vehicle is going uphill and should slow down to save energy, going downhill and should speed up to reduce travel time, or if the road grade is zero (0) then maintain the speed of the vehicle 10. The local optimization module 230 determines this as follows:

[0044] If the road slope < 0, ω veh_new =[1∶1.1]×ω veh

[0045] If the road slope > 0, ω veh_new =[0.9∶1]×ω veh

[0046] If the road slope = 0, ω veh_new =ω veh (4)

[0047] Among them, ω veh_new The corrected vehicle speed 232 for segment 304, ω veh A reference vehicle speed 306 for segment 304 is represented.

[0048] In addition to the road grade 218 , the local optimization module 230 generates a modified vehicle speed ω for each segment 304 of the baseline vehicle route profile 212 veh_new 232 may include external route data 204. For example, the external route data 204 may include at least one of headwind speed, traffic congestion along the vehicle route, or traffic signal information along the vehicle route. The external route data 204 may be detected by the vehicle 10 and / or may be received from a remote system 60 in communication with the vehicle 10 via the network 40. For example, traffic congestion may be detected using image data captured by a camera system of the vehicle 10. Additionally or alternatively, traffic congestion may be obtained via a satellite in communication with the remote system 60. Similarly, headwind speed may be received from a weather station in communication with the vehicle 10 and / or the remote system 10. Traffic signal information may be received from a traffic management agency in communication with the vehicle and / or the remote system 10.

[0049] The energy consumption model 240 may receive the modified vehicle speed ω for each segment 304 generated by the local optimization module 230 veh_new 232 as input, and by compiling the corrected vehicle speed ω of each segment 304 veh_new232 to generate an updated vehicle route profile 246 as an output. Thereafter, the global optimization module 250 may receive the baseline vehicle route profile 212 including the baseline energy consumption 242 and the baseline travel time 244 and the updated vehicle route profile 246 as inputs, and generate an optimized vehicle route profile 252 including an optimized energy consumption 254 and an optimized travel time 256 as output. Here, the optimized energy consumption 254 of the optimized vehicle route profile 252 is different from the baseline energy consumption 214 of the baseline vehicle route profile 212. The global optimization module 250 may execute an algorithm that further refines the updated vehicle route profile 246 along the vehicle route to minimize energy consumption and travel time interruptions, thereby identifying the best trade-off between energy consumption and travel time. For example, the global optimization module 250 may determine that modifying the vehicle speed during segments 304a, 304e, and 304f will increase the fuel efficiency of the vehicle 10 by 12% while only increasing the travel time of the vehicle 10 by 6 minutes, and generate the optimized vehicle route profile 252 to include the modified vehicle speed ω for segments 304a, 304e, and 304f. veh_new 232, while maintaining the reference vehicle speed ω of segments 304b-304f veh 306. In other examples, the global optimization module 250 may find the corresponding minimum fuel consumption value of the segment 304 based on the engine fuel consumption map and output the corresponding engine torque T e 214 and engine speed ω e 216 to calculate the gear ratio to maintain vehicle speed.

[0050] In some examples, the energy saving system 200 can provide the optimized vehicle route profile 252 to the vehicle controller of the vehicle 10. Here, the vehicle controller maintains the vehicle speed based on the input optimized vehicle route profile 252. Figure 1B In some embodiments, the global optimization module 250 determines that the difference between the optimized travel time 256 of the optimized vehicle route profile 252 and the baseline travel time 216 exceeds an acceptability threshold. For example, the manufacturer of the vehicle 10 may determine a route acceptability threshold that prevents the energy conservation system 200 from revising the baseline vehicle route profile 212 when the optimized vehicle route profile 252 will significantly increase the travel time of the vehicle 10 and / or does not significantly improve the fuel consumption of the vehicle. Here, when the difference between the optimized travel time 256 of the optimized vehicle route profile 252 and the baseline travel time 216 exceeds the acceptability threshold, the global optimization module 250 may not output the optimized vehicle route profile 252, but continue to process the baseline vehicle route profile 212.

[0051] Alternatively, if Figure 1BAs shown, the energy saving system 200 may generate a user selectable option 24 for output to the driver of the vehicle 10 (or the operator of the vehicle 10), which user selectable option 24 authorizes the optimized vehicle route profile 252 when selected. For example, the vehicle 10 may include or communicate with the user interface 20. Here, the user selectable option 24 may be output from the user interface 20 of the vehicle 10. As shown, the user interface 20 presents / displays a graphical element representing the user selectable option 24, "Do you want to save 8% energy if the estimated arrival time is increased by 5 minutes?" and includes a graphical element for the user to select "yes" or "no" before the vehicle 10 continues the optimized vehicle route profile 252. In response to the user selecting the graphical element "yes", the energy saving system 200 may provide the optimized vehicle route profile 252 to the vehicle controller of the vehicle 10.

[0052] Figure 4 A flow chart of an example operational arrangement of a method 400 for optimizing energy consumption of a vehicle 10 is included. At operation 402, the method 400 includes receiving vehicle route information 402. The method 400 also includes, at operation 404, generating a baseline vehicle route profile 212, the baseline vehicle route profile 212 including engine torque T e 214 and engine speed ω e 216. At operation 406, method 400 further includes determining the engine torque T based on the baseline vehicle route profile 212. e 214 and engine speed ω e 216 , generating a baseline energy consumption 242 and a baseline travel time 244 of the baseline vehicle route profile 212 .

[0053] The method 400 further includes, at operation 408, processing the baseline vehicle route profile 212 by detecting one or more changes in the road grade 218 of the baseline vehicle route profile 212. For each detected change in the road grade 218 of the baseline vehicle route profile 212, the method 400 further includes, at operation 410, triggering the breakpoint 302 to divide the baseline vehicle route profile 212 into the plurality of segments 304, 304a-n. Here, each respective segment 304 in the plurality of segments 304 has a baseline vehicle speed 306.

[0054] For each respective segment 304 of the plurality of segments 304 of the baseline vehicle route profile 212, the method 400 further includes, at operation 412, performing a local optimization on the baseline vehicle speed 306 to generate a revised vehicle speed 232. At operation 414, the method 400 further includes, based on the revised vehicle speed 232 of each respective segment 304 of the plurality of segments 304, generating an updated vehicle route profile 446. The method 400 further includes, at operation 416, performing a global optimization on the updated vehicle route profile 446 to generate an optimized vehicle route profile 252. The optimized vehicle route profile 252 includes an optimized energy consumption 254 that is different from the baseline energy consumption 214 of the baseline vehicle route profile 212.

[0055] Many embodiments have been described. However, it should be understood that various modifications can be made without departing from the spirit and scope of the present disclosure. Therefore, other embodiments are also within the scope of the following claims.

[0056] The foregoing description has been provided for the purpose of illustration and description. It is not intended to be exhaustive or to limit the present disclosure. Individual elements or features of a particular configuration are generally not limited to that particular configuration, but where applicable, they are interchangeable and can be used in a selected configuration even if not specifically shown or described. This can also be varied in a variety of ways. Such variations should not be considered a departure from the present disclosure, and all such modifications are intended to be included within the scope of the present disclosure.

Claims

1. A computer-implemented method which, when executed on data processing hardware, causes the data processing hardware to perform operations comprising: receiving vehicle route information; generating a baseline vehicle route profile, the baseline vehicle route profile comprising engine torque and engine speed; generating a baseline energy consumption and a baseline travel time for the baseline vehicle route profile based on the engine torque and the engine speed of the baseline vehicle route profile; processing a baseline vehicle route profile by detecting one or more changes in a road grade of the baseline vehicle route profile; for each detected change in the road grade of the baseline vehicle route profile, triggering a breakpoint to divide the baseline vehicle route profile into a plurality of segments, each respective segment of the plurality of segments having a baseline vehicle speed; for each respective segment of the plurality of segments of the baseline vehicle route profile, performing a local optimization to generate a revised vehicle speed; generating an updated vehicle route profile based on the revised vehicle speed for each of the plurality of segments; as well as A global optimization is performed on the updated vehicle route profile to generate an optimized vehicle route profile having an optimized energy consumption different from a baseline energy consumption of the baseline vehicle route profile.

2. The method according to claim 1, wherein: The operations also include providing the optimized vehicle route profile to a vehicle controller.

3. The method according to claim 1, wherein: The vehicle route information includes at least one of the following: Roadmap data; Route slope data; The vehicle's headwind speed; or Vehicle local data.

4. The method according to claim 1, wherein: The vehicle local data includes at least one of the following: Vehicle quality; Powertrain data; The vehicle's transmission gear ratio; or Vehicle aerodynamic coefficients.

5. The method according to claim 1, wherein: Performing a local optimization to generate a corrected vehicle speed includes: Receive external route data; Determining that the road slope is negative; and The base vehicle speed is increased based on the variance factor and external route data.

6. The method according to claim 5, wherein: The external route data includes at least one of the following: Headwind speed; Traffic congestion; or Traffic signal information.

7. The method according to claim 1, wherein: Performing a local optimization to generate a corrected vehicle speed includes: Receive external route data; Determining that the road slope is positive; and The base vehicle speed is reduced based on the variance factor and the external route data.

8. The method according to claim 7, wherein: The external route data includes at least one of the following: Headwind speed; Traffic congestion; or Traffic signal information.

9. The method according to claim 1, wherein: The operations also include: determining that a difference between an optimized travel time and a benchmark travel time for the optimized vehicle route profile exceeds an acceptability threshold; and A user selectable option is generated for output to the driver, the user selectable option authorizing the optimized vehicle route profile when selected.

10. The method according to claim 9, wherein: The user selectable options are provided as output from a vehicle user interface.

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