Energy management method and system for electric vehicle, storage medium, terminal

Abstract

The application discloses an energy management method and system of an electric vehicle, a storage medium and a terminal, relates to the technical field of vehicle development, and mainly aims to improve the technical problem that the maximization of energy utilization is difficult to realize due to single algorithm, low intelligent degree and the like, energy utilization is low, and vehicle endurance mileage is reduced. The method comprises the following steps: acquiring current road condition information, driving information, vehicle information and demand acceleration parameter data of the vehicle; determining demand braking force parameter data of the vehicle according to the current road condition information, driving information, vehicle information and demand acceleration parameter data; outputting target braking force parameter data of the vehicle according to the demand braking force parameter data and maximum braking force parameter data that can be provided by the vehicle currently, so as to control driving of the vehicle according to the target braking force parameter data.

Description

Technical Field

[0001] This application relates to the field of vehicle research and development technology, and in particular to an energy management method, system, storage medium, and terminal for electric vehicles. Background Technology

[0002] As people increasingly value environmental issues, new energy vehicles, as a lower-carbon and environmentally friendly mode of transportation compared to traditional fuel vehicles, have received widespread attention. In research on new energy vehicles, improving the performance of energy storage devices and increasing energy utilization efficiency are two crucial aspects. However, improving the performance of energy storage devices is constrained by factors such as economics and safety, making significant breakthroughs difficult to achieve in the short term. Therefore, given the current lack of major breakthroughs in new energy vehicle energy storage technology, improving energy utilization efficiency has become a critical technical challenge.

[0003] Currently, existing technologies mainly rely on analyzing the driver's braking intentions through driver feedback to further deduce the operational intent and thus control the vehicle's movement. However, in developing this invention, the inventors discovered at least the following problems with existing technologies: due to their simplistic algorithms and low level of intelligence, it is difficult to maximize energy utilization, resulting in low energy efficiency and consequently reduced vehicle range. Summary of the Invention

[0004] In view of this, this application provides an energy management method, system, storage medium, and terminal for electric vehicles. The main purpose is to improve the existing technical problems that make it difficult to maximize energy utilization due to the single algorithm and low level of intelligence, resulting in low energy utilization and thus reduced vehicle range.

[0005] According to one aspect of this application, an energy management method for an electric vehicle is provided, comprising:

[0006] Obtain current road condition information, driving information, vehicle information, and required acceleration parameter data for the vehicle;

[0007] Based on the current road condition information, driving information, vehicle information, and required acceleration parameter data, determine the current required braking force parameter data of the vehicle;

[0008] Based on the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide, the current target braking force parameter data of the vehicle is output, so as to control the vehicle to drive according to the target braking force parameter data.

[0009] Preferably, before determining the current required braking force parameters of the vehicle based on the current road condition information, driving information, vehicle information, and required acceleration parameter data, the method further includes:

[0010] The current road condition information, driving information, and vehicle information are subjected to multi-objective fusion processing of physics and mechanics to obtain the current uniform speed negative torque parameter data of the vehicle.

[0011] Preferably, determining the vehicle's current required braking force parameters based on the current road condition information, driving information, vehicle information, and required acceleration parameter data specifically includes:

[0012] The vehicle's current uniform negative torque parameter data and the required acceleration parameter data are processed by dynamic calculations to determine the vehicle's current required braking force parameter data.

[0013] Preferably, before outputting the current target braking force parameter data of the vehicle based on the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide, the method further includes:

[0014] The first braking force parameter data is determined based on the vehicle's current driving information and motor power information;

[0015] The second braking force parameter data is determined based on the vehicle's current driving information and battery recharge power information.

[0016] The braking force parameter data with the smaller value between the first braking force parameter data and the second braking force parameter data is selected as the maximum braking force parameter data that the vehicle can currently provide.

[0017] Preferably, the step of outputting the current target braking force parameter data of the vehicle based on the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide specifically includes:

[0018] The smaller value of the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide is selected as the current target braking force parameter data of the vehicle and output.

[0019] Preferably, after acquiring the vehicle's current road condition information, driving information, vehicle information, and required acceleration parameter data, the method further includes:

[0020] The road condition information is filtered to enable multi-objective fusion processing based on the filtered road condition information.

[0021] Preferably, after acquiring the vehicle's current road condition information, driving information, vehicle information, and required acceleration parameter data, the method further includes:

[0022] The required acceleration parameter data is subjected to stability processing so that dynamic calculations can be performed based on the stabilized required acceleration parameter data.

[0023] According to another aspect of this application, an energy management system for an electric vehicle is provided, comprising:

[0024] The acquisition module is used to acquire the vehicle's current road condition information, driving information, vehicle information, and required acceleration parameter data;

[0025] The determination module is used to determine the current required braking force parameters of the vehicle based on the current road condition information, driving information, vehicle information, and required acceleration parameter data.

[0026] The control module is used to output the current braking force parameters of the vehicle based on the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide.

[0027] Preferably, before the determining module, the system further includes:

[0028] The fusion module is used to perform physical and mechanical multi-objective fusion processing on the current road condition information, driving information, and vehicle information to obtain the current uniform speed negative torque parameter data of the vehicle.

[0029] Preferably, the determining module is specifically used for:

[0030] The vehicle's current uniform negative torque parameter data and the required acceleration parameter data are processed by dynamic calculations to determine the vehicle's current required braking force parameter data.

[0031] Preferably, prior to the control module, the system further includes:

[0032] The calculation module is used to determine the first braking force parameter data based on the vehicle's current driving information and motor power information;

[0033] The calculation module is also used to determine the second braking force parameter data based on the vehicle's current driving information and battery recharge power information;

[0034] The selection module is used to select the braking force parameter data with the smaller value between the first braking force parameter data and the second braking force parameter data as the maximum braking force parameter data that the vehicle can currently provide.

[0035] Preferably, the control module is specifically used for:

[0036] The smaller value of the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide is selected as the current target braking force parameter data of the vehicle and output.

[0037] Preferably, after the acquisition module, the system further includes:

[0038] The filtering module is used to filter the road condition information so that physical and mechanical multi-objective fusion processing can be performed based on the filtered road condition information.

[0039] Preferably, after the acquisition module, the system further includes:

[0040] The stabilization module is used to perform stability processing on the required acceleration parameter data, so that dynamic calculations can be performed based on the stabilized required acceleration parameter data.

[0041] According to another aspect of this application, a storage medium is provided that stores at least one executable instruction, which causes a processor to perform an operation corresponding to the energy management method for electric vehicles described above.

[0042] According to another aspect of this application, a terminal is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus;

[0043] The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the energy management method of the electric vehicle described above.

[0044] By employing the above technical solutions, the technical solutions provided in the embodiments of this application have at least the following advantages:

[0045] This application provides an energy management method, system, storage medium, and terminal for electric vehicles. First, it acquires current road condition information, driving information, vehicle information, and required acceleration parameter data. Second, based on the current road condition information, driving information, vehicle information, and required acceleration parameter data, it determines the current required braking force parameter data for the vehicle. Finally, based on the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide, it outputs the current target braking force parameter data for the vehicle, thereby controlling the vehicle's movement according to the target braking force parameter data. Compared with existing technologies, this application's embodiment fuses multi-dimensional factors such as road condition information, driving information, and vehicle information to determine uniform speed negative torque parameter data, then determines the vehicle's current required braking force parameter data based on the uniform speed negative torque parameter data and required acceleration parameter data; further, it combines the maximum braking force parameter data that the vehicle can currently provide to determine the final target braking force parameter data, and controls the vehicle based on the target braking force parameter data. This fully utilizes the multi-dimensional factors affecting the maximization of energy utilization, achieving maximum energy utilization, improving energy efficiency, and increasing the vehicle's driving range.

[0046] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0047] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0048] Figure 1 A flowchart of an energy management method for an electric vehicle, as provided in one embodiment of the present invention;

[0049] Figure 2 A flowchart of another energy management method for an electric vehicle provided as an embodiment of the present invention;

[0050] Figure 3 A flowchart illustrating the overall process of vehicle control according to an embodiment of the present invention;

[0051] Figure 4 A block diagram of an energy management system for an electric vehicle, provided as an embodiment of the present invention;

[0052] Figure 5This is a schematic diagram of the structure of a terminal according to an embodiment of the present invention. Detailed Implementation

[0053] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0054] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0055] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the scope of this application and its application or use.

[0056] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0057] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0058] The embodiments of this application can be applied to computer systems / servers that can operate with a wide range of other general-purpose or special-purpose computing system environments or configurations. Examples of well-known computing systems, environments, and / or configurations suitable for use with computer systems / servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems, etc.

[0059] Computer systems / servers can be described in the general context of computer system executable instructions (such as program modules) executed by the computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are performed by remote processing devices linked through a communication network. In distributed cloud computing environments, program modules can reside on local or remote computing system storage media, including storage devices.

[0060] This application provides an energy management method for electric vehicles, such as... Figure 1 As shown, the method includes:

[0061] 101. Obtain the vehicle's current road condition information, driving information, vehicle information, and required acceleration parameter data.

[0062] Among them, road condition information is used to characterize the slope of the road the vehicle is currently on; driving information is used to characterize the vehicle's current speed; vehicle information includes, but is not limited to, the vehicle's current load information, motor power information, and battery recharge power information; and required acceleration parameter data is used to characterize the acceleration parameter data required to adjust the vehicle speed, for example, the acceleration parameter data generated when the driver accelerates or decelerates the vehicle by operating the vehicle's cruise control switch. In this embodiment, the current execution end can be the vehicle's energy management system, and the vehicle can be a pure electric vehicle or a hybrid vehicle, including civilian vehicles and mining wide-body vehicles, etc., without specific limitations in this embodiment.

[0063] It should be noted that the current execution end can use the vehicle's VCU system as the hardware core. Through a hardware platform composed of the vehicle's onboard slope sensor, weight sensor, and vehicle controller, it can acquire real-time road condition information, driving information, vehicle information, and required acceleration parameter data. Specifically, the slope sensor is responsible for collecting the vehicle's current road condition information; the weight sensor is responsible for collecting the vehicle's current load information; and the vehicle controller is responsible for collecting the vehicle's current motor power information, battery recharge power information, current driving information, and required acceleration parameter data.

[0064] 102. Based on the current road conditions, driving information, vehicle information, and required acceleration parameter data, determine the vehicle's current required braking force parameter data.

[0065] The current required braking force parameter data of the vehicle is used to characterize the braking force parameter data required to control the vehicle to reach the required acceleration parameter data. In this embodiment, the current required acceleration parameter data of the vehicle is converted into the braking force parameter data required for the vehicle to travel at this acceleration, that is, the braking force parameter data required to control the vehicle to reach the required acceleration parameter data.

[0066] 103. Based on the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide, output the current target braking force parameter data of the vehicle, so as to control the vehicle to drive according to the target braking force parameter data.

[0067] It should be noted that, on the one hand, the actual maximum electric braking force that the motor can provide varies due to differences in vehicle speed; on the other hand, the real-time changes in battery temperature and charge cause changes in battery recharge power, which in turn cause the actual maximum electric braking force that the battery can provide to change in real time. Therefore, the maximum braking force parameter that the vehicle can currently provide may not meet the vehicle's current braking force requirements. Thus, it is necessary to select the smaller of the two values ​​as the target braking force parameter and use it to control vehicle movement.

[0068] Compared with existing technologies, the embodiments of this application determine the uniform-speed negative torque parameter data by fusing multi-dimensional factors such as road condition information, driving information, and vehicle information. Then, based on the uniform-speed negative torque parameter data and the required acceleration parameter data, the current required braking force parameter data of the vehicle is determined. Furthermore, by combining the maximum braking force parameter data that the vehicle can currently provide, the final target braking force parameter data is determined, and the vehicle is controlled based on the target braking force parameter data. This fully utilizes the multi-dimensional factors affecting the maximization of energy utilization.

[0069] This application provides another energy management method for electric vehicles, such as... Figure 2 As shown, the method includes:

[0070] 201. Obtain the vehicle's current road condition information, driving information, vehicle information, and required acceleration parameter data.

[0071] In this embodiment, the current execution end can use the vehicle's VCU system as the hardware core. Through a hardware platform composed of a slope sensor, a weight sensor, and a vehicle controller, it can acquire real-time road condition information, driving information, vehicle information, and required acceleration parameter data. For example, when acquiring vehicle load information, two suspension cylinder pressure sensors can be installed on the front suspension and four on the rear suspension to collect pressure data. A weighing system is then built using Matlab / Simulink, and the load capacity of the cargo box is calculated based on the collected suspension cylinder pressure and force area, thus obtaining the vehicle's current load information. When acquiring road condition information, a sensor can be placed in the cab to measure the acceleration and angular velocity values ​​along the X, Y, and Z axes. A slope calculation system is then built using Matlab / Simulink to calculate the slope value, i.e., the vehicle's current road condition information. The vehicle information, including the vehicle's current motor power, battery recharge power, and current driving information, can be acquired by the vehicle controller.

[0072] As a preferred approach, the current road condition information of the vehicle obtained in step 201 of the embodiment can be filtered to enable physical and mechanical multi-objective fusion processing based on the filtered road condition information.

[0073] It should be noted that if the current execution end is the energy management system of a wide-body mining vehicle, considering the complex and variable slope conditions of heavy-load downhill roads in mining areas, the real-time road condition information may experience jumps and repeated oscillations, leading to oscillations in the vehicle motor torque. To avoid these problems, the collected road condition information can be filtered (e.g., RC filtering or mean filtering) to stabilize the road condition information and reduce the probability of torque oscillations. Specifically, filtering can be performed according to the following formula.

[0074] Y(n)=2πtF*X(n)+(1-2πtF)*Y(n-1)

[0075] Where t represents the signal period, F represents the cutoff frequency, X(n) represents the input value of the current period, and Y(n-1) represents the output value of the previous period.

[0076] As another preferred solution, the demand acceleration parameter data obtained in step 201 of the embodiment can be subjected to stability processing so that dynamic calculation processing can be performed based on the demand acceleration parameter data after stability processing.

[0077] It should be noted that if the current execution end is the energy management system of a wide-body mining vehicle, considering the complex and variable road conditions in mining areas, in order to ensure smooth acceleration and driving comfort, the required acceleration parameter data can be pre-processed for stability, for example, through a PI control algorithm. Specifically, the core formula of the PI control algorithm is as follows:

[0078]

[0079] Where u(t) represents the output curve, i.e., the curve of the PID output value changing over time, and K P T represents the proportionality coefficient, e(t) represents the deviation curve, that is, the curve showing the change of the deviation between the set value and the actual value over time. I Indicates the integration time.

[0080] 202. Perform physical and mechanical multi-objective fusion processing on the current road condition information, driving information, and vehicle information to obtain the current uniform speed negative torque parameter data of the vehicle.

[0081] In this embodiment, the vehicle's current uniform-speed negative torque parameters are calculated by fusing multiple dimensions such as road condition information, driving information, and vehicle information. Specifically, the core formula for the multi-objective fusion processing of physics and mechanics is as follows:

[0082]

[0083] Where m represents the vehicle's load information, g represents gravitational acceleration, α represents the gradient, r represents the rolling radius, io represents the final drive ratio, ng represents the wheel-end speed, and C D The value represents the air resistance coefficient, and A represents the frontal area.

[0084] 203. Perform dynamic calculations on the vehicle's current uniform speed negative torque parameter data and required acceleration parameter data to determine the vehicle's current required braking force parameter data.

[0085] In this embodiment, the current required acceleration parameter data of the vehicle is converted into braking force parameter data required for the vehicle to travel at this acceleration, that is, braking force parameter data required to control the vehicle to reach the required acceleration parameter data. Specifically, the core formula for dynamics calculation is as follows:

[0086] F 需求制动力参数数据 =F 匀速负扭矩参数数据 +ma

[0087] Where m represents the vehicle's load information, and a represents the required acceleration parameter data.

[0088] 204. Determine the maximum braking force parameters that the vehicle can currently provide.

[0089] In this embodiment, specifically, firstly, based on the motor power information, the gear ratios of each gearbox, and the current driving information, the maximum braking capacity that the motor-gearbox assembly can provide at the same output shaft speed can be determined using the following formula.

[0090]

[0091] Where N1 represents the maximum electric braking force that the motor can provide, i.e., the first braking force parameter data, P represents the motor power information, V represents the driving information, and i0 represents the vehicle's final reduction ratio.

[0092] Furthermore, based on the voltage and current information of the battery cells and the cell arrangement design, the maximum braking capacity that the battery can provide can be determined using the following formula.

[0093]

[0094] Where N2 represents the maximum electric braking force that the battery can provide, i.e., the second braking force parameter data, u represents the voltage information of the battery cell, i represents the current information of the battery cell, V represents the driving information, and i0 represents the vehicle's final reduction ratio.

[0095] Finally, the braking force parameter with the smaller value between the first braking force parameter data and the second braking force parameter data is selected as the maximum braking force parameter data that the vehicle can currently provide.

[0096] Accordingly, step 204 of the embodiment specifically includes: determining the first braking force parameter data based on the vehicle's current driving information and motor power information; determining the second braking force parameter data based on the vehicle's current driving information and battery recharge power information; and selecting the braking force parameter data with the smaller value between the first braking force parameter data and the second braking force parameter data as the maximum braking force parameter data that the vehicle can currently provide.

[0097] 205. Select the braking force parameter data with the smaller value between the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide as the current target braking force parameter data of the vehicle and output it.

[0098] In this embodiment, on the one hand, the actual maximum electric braking force that the motor can provide varies due to different vehicle speeds; on the other hand, the real-time changes in battery temperature and charge cause changes in battery recharge power, which in turn cause the actual maximum electric braking force that the battery can provide to change in real time. Therefore, the maximum braking force parameter data that the vehicle can currently provide may not meet the vehicle's current braking force parameter data. Therefore, it is necessary to select the smaller of the two values ​​as the target braking force parameter data and control the vehicle's movement accordingly.

[0099] In specific application scenarios, such as Figure 3 As shown, firstly, based on the vehicle's current speed, load weight, and gradient after RC filtering, a multi-objective fusion processing of physics and mechanics is performed to obtain the vehicle's current required uniform negative torque value; then, combined with the driver's required acceleration, the vehicle's current required braking force parameter data is determined; secondly, based on the vehicle's current battery power and motor power, the maximum braking force that the vehicle can currently provide is determined; finally, based on the vehicle's current required braking force parameter data and the vehicle's current maximum braking force, the target braking force parameter data is determined, and the vehicle's movement is controlled according to the target braking force parameter data.

[0100] This application provides an energy management method for electric vehicles. First, it acquires current road condition information, driving information, vehicle information, and required acceleration parameter data. Second, based on the current road condition information, driving information, vehicle information, and required acceleration parameter data, it determines the current required braking force parameter data for the vehicle. Finally, based on the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide, it outputs the current target braking force parameter data for the vehicle, thereby controlling the vehicle's movement according to the target braking force parameter data. Compared with existing technologies, this application's embodiment fuses multi-dimensional factors such as road condition information, driving information, and vehicle information to determine uniform speed negative torque parameter data, then determines the vehicle's current required braking force parameter data based on the uniform speed negative torque parameter data and required acceleration parameter data; further, it combines the maximum braking force parameter data that the vehicle can currently provide to determine the final target braking force parameter data, and controls the vehicle based on the target braking force parameter data. This fully utilizes the multi-dimensional factors affecting the maximization of energy utilization, achieving maximum energy utilization, improving energy efficiency, and increasing the vehicle's driving range.

[0101] Furthermore, as a response to the above Figure 1 The implementation of the method shown in this application provides an energy management system for electric vehicles, such as... Figure 4 As shown, the system includes:

[0102] Acquisition module 31, determination module 32, control module 33.

[0103] The acquisition module 31 is used to acquire the vehicle's current road condition information, driving information, vehicle information, and required acceleration parameter data;

[0104] The determining module 32 is used to determine the current required braking force parameter data of the vehicle based on the current road condition information, driving information, vehicle information and required acceleration parameter data;

[0105] Control module 33 is used to output the current braking force parameter data of the vehicle based on the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide.

[0106] In specific application scenarios, prior to the determining module, the system further includes:

[0107] The fusion module is used to perform physical and mechanical multi-objective fusion processing on the current road condition information, driving information, and vehicle information to obtain the current uniform speed negative torque parameter data of the vehicle.

[0108] In specific application scenarios, the determining module is specifically used for:

[0109] The vehicle's current uniform negative torque parameter data and the required acceleration parameter data are processed by dynamic calculations to determine the vehicle's current required braking force parameter data.

[0110] In specific application scenarios, before the control module, the system further includes:

[0111] The calculation module is used to determine the first braking force parameter data based on the vehicle's current driving information and motor power information;

[0112] The calculation module is also used to determine the second braking force parameter data based on the vehicle's current driving information and battery recharge power information;

[0113] The selection module is used to select the braking force parameter data with the smaller value between the first braking force parameter data and the second braking force parameter data as the maximum braking force parameter data that the vehicle can currently provide.

[0114] In specific application scenarios, the control module is specifically used for:

[0115] The smaller value of the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide is selected as the current target braking force parameter data of the vehicle and output.

[0116] In specific application scenarios, after the acquisition module, the system further includes:

[0117] The filtering module is used to filter the road condition information so that physical and mechanical multi-objective fusion processing can be performed based on the filtered road condition information.

[0118] In specific application scenarios, after the acquisition module, the system further includes:

[0119] The stabilization module is used to perform stability processing on the required acceleration parameter data, so that dynamic calculations can be performed based on the stabilized required acceleration parameter data.

[0120] This application provides an energy management system for electric vehicles. First, it acquires current road condition information, driving information, vehicle information, and required acceleration parameter data. Second, based on the current road condition information, driving information, vehicle information, and required acceleration parameter data, it determines the current required braking force parameter data for the vehicle. Finally, based on the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide, it outputs the current target braking force parameter data for the vehicle, thereby controlling the vehicle's movement according to the target braking force parameter data. Compared with existing technologies, this application's embodiment fuses multi-dimensional factors such as road condition information, driving information, and vehicle information to determine uniform speed negative torque parameter data. Then, it determines the vehicle's current required braking force parameter data based on the uniform speed negative torque parameter data and required acceleration parameter data. Furthermore, it combines this with the maximum braking force parameter data that the vehicle can currently provide to determine the final target braking force parameter data, and controls the vehicle based on the target braking force parameter data. This fully utilizes the multi-dimensional factors affecting the maximization of energy utilization, achieving maximum energy utilization, improving energy efficiency, and increasing the vehicle's driving range.

[0121] According to one embodiment of this application, a storage medium is provided, the storage medium storing at least one executable instruction that can execute the energy management method for an electric vehicle in any of the above method embodiments.

[0122] Based on this understanding, the technical solution of this application can be embodied in the form of a software product. This software product can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, or portable hard drive), and includes several instructions to cause a computer device (such as a personal computer, server, or network device) to execute the methods described in the various implementation scenarios of this application.

[0123] Figure 5 The diagram shows a structural schematic of a terminal according to one embodiment of the present application. The specific embodiments of the present application do not limit the specific implementation of the terminal.

[0124] like Figure 5 As shown, the computer device may include: a processor 402, a communications interface 404, a memory 406, and a communications bus 408.

[0125] The processor 402, communication interface 404, and memory 406 communicate with each other via communication bus 408.

[0126] Communication interface 404 is used to communicate with other network elements such as clients or other servers.

[0127] The processor 402 is used to execute program 410, specifically to execute the relevant steps in the above-described embodiment of the energy management method for electric vehicles.

[0128] Specifically, program 410 may include program code that includes computer operation instructions.

[0129] Processor 402 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application. The computer device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or they may be processors of different types, such as one or more CPUs and one or more ASICs.

[0130] Memory 406 is used to store program 410. Memory 406 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0131] Specifically, program 410 can be used to cause processor 402 to perform the following operations:

[0132] Obtain current road condition information, driving information, vehicle information, and required acceleration parameter data for the vehicle;

[0133] Based on the current road condition information, driving information, vehicle information, and required acceleration parameter data, determine the current required braking force parameter data of the vehicle;

[0134] Based on the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide, the current target braking force parameter data of the vehicle is output, so as to control the vehicle to drive according to the target braking force parameter data.

[0135] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the energy management entity of the aforementioned electric vehicle, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software in the information processing entity.

[0136] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0137] The methods and systems of this application may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of this application are not limited to the order specifically described above, unless otherwise specifically stated. Furthermore, in some embodiments, this application may also be implemented as a program recorded on a recording medium, the program including machine-readable instructions for implementing the methods according to this application. Thus, this application also covers recording media storing programs for performing the methods according to this application.

[0138] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0139] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. An energy management method for electric vehicles, characterized in that, include: Obtain current road condition information, driving information, vehicle information, and required acceleration parameter data for the vehicle; The current road condition information, driving information, and vehicle information are subjected to a multi-objective fusion processing based on physics and mechanics to obtain the current uniform speed negative torque parameter data of the vehicle. The core formula of the multi-objective fusion processing based on physics and mechanics is as follows: Where m represents the vehicle's load information, g represents gravitational acceleration, α represents the slope, r represents the rolling radius, and i o Indicates the final drive ratio, n g Indicates the wheel end speed. The value represents the air resistance coefficient, and A represents the frontal area. The vehicle's current uniform speed negative torque parameter data and the required acceleration parameter data are processed by dynamic calculation to determine the vehicle's current required braking force parameter data. Based on the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide, the current target braking force parameter data of the vehicle is output, so as to control the vehicle to drive according to the target braking force parameter data.

2. The method according to claim 1, characterized in that, Before outputting the current target braking force parameter data of the vehicle based on the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide, the method further includes: The first braking force parameter data is determined based on the vehicle's current speed information and motor power information. The second braking force parameter data is determined based on the vehicle's current speed information and the battery recharge power information. The braking force parameter data with the smaller value between the first braking force parameter data and the second braking force parameter data is selected as the maximum braking force parameter data that the vehicle can currently provide.

3. The method according to claim 2, characterized in that, The step of outputting the vehicle's current target braking force parameter data based on the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide specifically includes: The smaller value of the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide is selected as the current target braking force parameter data of the vehicle and output.

4. The method according to claim 1, characterized in that, After acquiring the vehicle's current road condition information, driving information, vehicle information, and required acceleration parameter data, the method further includes: The slope information is filtered to enable multi-objective fusion processing of physical and mechanical aspects based on the filtered road condition information.

5. The method according to claim 1, characterized in that, After acquiring the vehicle's current road condition information, driving information, vehicle information, and required acceleration parameter data, the method further includes: The required acceleration parameter data is subjected to stability processing so that dynamic calculations can be performed based on the stabilized required acceleration parameter data.

6. An energy management system for an electric vehicle, characterized in that, include: The acquisition module is used to acquire the vehicle's current road condition information, driving information, vehicle information, and required acceleration parameter data; The fusion module is used to perform multi-objective physics and mechanics fusion processing on the current road condition information, driving information, and vehicle information to obtain the current uniform speed negative torque parameter data of the vehicle. The core formula of the multi-objective physics and mechanics fusion processing is as follows: Where m represents the vehicle's load information, g represents gravitational acceleration, α represents the slope, r represents the rolling radius, and i o Indicates the final drive ratio, n g Indicates the wheel end speed. The value represents the air resistance coefficient, and A represents the frontal area. The determination module is used to perform dynamic calculations on the current uniform speed negative torque parameter data and the required acceleration parameter data of the vehicle to determine the current required braking force parameter data of the vehicle. The control module is used to output the current target braking force parameter data of the vehicle based on the required braking force parameter data and the maximum braking force parameter data that the vehicle can currently provide, so as to control the vehicle to drive according to the target braking force parameter data.

7. A storage medium storing at least one executable instruction, characterized in that, The executable instructions cause the processor to perform the operations corresponding to the energy management method for electric vehicles as described in any one of claims 1-5.

8. A terminal, comprising: A processor and a memory, wherein a communication connection is established between the processor and the memory; The memory is used to store at least one executable instruction, characterized in that the executable instruction causes the processor to perform an operation corresponding to the energy management method for an electric vehicle as described in any one of claims 1-5.

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