An electric vehicle energy management method, a terminal device, and a storage medium

Abstract

The present application relates to a kind of electric vehicle energy management method, terminal device and storage medium, the method includes: real-time according to electronic horizon data calculates predictive dynamic threshold value, and according to predictive dynamic threshold value set electric vehicle battery and supercapacitor energy output and recovery ratio.The present application predicts the road ahead based on electronic horizon system, generates predictive dynamic logic threshold value according to electronic horizon information, changes the defect that conventional fixed logic threshold value does not have predictive optimal energy management, sets corresponding energy management strategy according to predictive dynamic logic threshold value to carry out predictive performance energy management, reduces the energy consumption of electric vehicle and prevents battery loss, improves vehicle economy and can play an active role.

Description

Technical Field

[0001] The present invention relates to the field of energy management, and in particular to an electric vehicle energy management method, terminal equipment, and storage medium. Background Art

[0002] The energy system of a modern pure electric vehicle generally consists of batteries and supercapacitors, which require energy management. The goal is to rationally allocate the power output of the battery and supercapacitor to meet the power requirements of the vehicle's operation, fully utilize the characteristics and advantages of the battery and supercapacitor, and maximize the battery life and reduce energy loss. The general principle is to leverage the supercapacitor's advantage of instantaneous high-power charging and discharging to avoid the impact of instantaneous high-current discharge on lithium batteries during vehicle acceleration, thereby extending the battery life. When the power required by the vehicle is low, it is powered solely by the battery. When the power required by the vehicle is high, the battery provides a basic amount of power, and the excess is provided by the supercapacitor. When the vehicle brakes, the high-power energy is first recovered by the highly efficient supercapacitor to avoid high-current charging and damage to the battery. When the supercapacitor is fully charged, the energy is recovered by the battery.

[0003] The most common energy management approach is a logic threshold rule-based energy management strategy. This strategy sets a series of vehicle operating parameters and the logic thresholds (PL) for power output or recovery. It then categorizes the vehicle's operating states to determine the energy management strategy for each operating state. However, current rule-based strategies only consider the vehicle's current power requirements and fail to predict future power demands. This can result in energy management that is reasonable under current conditions but suboptimal in future operations. Energy management cannot be adjusted promptly based on potential changes in road conditions, hindering the ability to more effectively reduce EV energy consumption and prevent battery loss. Summary of the Invention

[0004] In order to solve the above problems, the present invention proposes an electric vehicle energy management method, a terminal device and a storage medium.

[0005] The specific plan is as follows:

[0006] An electric vehicle energy management method includes: calculating a predictive dynamic threshold value based on electronic horizon data in real time, and setting the energy output and recovery ratio of the electric vehicle battery and supercapacitor according to the predictive dynamic threshold value.

[0007] Furthermore, the predictive dynamic threshold is calculated based on the average slope of the road ahead, the distance between the vehicle's current position and the slope, and the fixed logic threshold.

[0008] Furthermore, the predictive dynamic threshold P' L The calculation formula is:

[0009]

[0010] Among them, S represents the average slope of the road ahead of the vehicle's current position, D represents the distance between the vehicle's current position and the slope, and P L Indicates a fixed logic threshold value, A and M are constants, and u is a step function.

[0011] Furthermore, A is

[0012] Furthermore, the specific process of setting the energy output and recovery ratio of the electric vehicle battery and supercapacitor according to the predictive dynamic threshold value is as follows:

[0013] Based on the throttle depth and the current vehicle speed, the power Pn required for vehicle operation at the current moment is obtained. At the same time, the current battery capacity BSOC and supercapacitor capacity USOC are obtained, and the following judgments are made:

[0014] When Pn<0 and USOC>USOC H When , set the battery power Pb = Pn, and the supercapacitor power Pc = 0;

[0015] When Pn<0 and USOC≤USOC H When setting, set the battery power Pb = 0 and the supercapacitor power Pc = Pn;

[0016] When 0≤P n ≤P' L 、USOC>USOC L And BSOC>BSOC L When , set the battery power Pb = Pn, and the supercapacitor power Pc = 0;

[0017] When P n >P' L 、USOC>USOC L And BSOC>BSOC L When setting the battery power P b =P' L , supercapacitor power P c =P n -P' L ;

[0018] When Pn>0, USOC≤USOC L And BSOC>BSOC L When , set the battery power Pb = Pn, and the supercapacitor power Pc = 0;

[0019] When Pn>0, USOC>USOC L And BSOC≤BSOC LWhen Pn>0, USOC

[0020] When Pn>0, USOC L and BSOC L , set battery power Pb=0, super capacitor power Pc=0.

[0021] Wherein, USOC H and USOC L respectively represent the upper limit value and the lower limit value of the super capacitor SOC electric quantity. BSOC L represents the lower limit value of the lithium battery SOC electric quantity.

[0022] An electric vehicle energy management terminal device, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method of the above-mentioned embodiment of the application when executing the computer program.

[0023] A computer readable storage medium, the computer readable storage medium stores a computer program, wherein the computer program is executed by a processor to implement the steps of the method of the above-mentioned embodiment of the application.

[0024] The present application adopts the above technical solution, predicts the terrain in front based on the electronic horizon system, generates a predictive dynamic logic threshold value according to the electronic horizon information, changes the conventional fixed logic threshold value which has the defect of non-predictive optimal energy management, sets a corresponding energy management strategy according to the predictive dynamic logic threshold value to perform predictive energy management, reduces the energy consumption of the electric vehicle and prevents battery loss, and improves the economy of the vehicle and the like. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 The flowchart of the first embodiment of the present application is shown. DETAILED DESCRIPTION

[0026] To further illustrate the embodiments, the present application provides accompanying drawings. These drawings are part of the disclosure of the present application, mainly used to illustrate the embodiments, and can be used to explain the operating principle of the embodiments in conjunction with the related description of the specification. With reference to these contents, those skilled in the art should understand other possible embodiments and advantages of the present application.

[0027] The present application will be further described in conjunction with the accompanying drawings and specific embodiments.

[0028] Embodiment one:

[0029] The embodiment of the present application provides an electric vehicle energy management method, such as Figure 1As shown, the method is: calculating the predictive dynamic threshold value based on the electronic horizon data in real time, and setting the energy output and recovery ratio of the electric vehicle battery and supercapacitor according to the predictive dynamic threshold value.

[0030] This embodiment uses electronic horizon data to generate predictive dynamic threshold values, which changes the defect of conventional fixed logic threshold values ​​that do not have predictive optimal energy management, optimizes energy management, makes energy distribution between batteries and supercapacitors more reasonable, improves the energy utilization efficiency of the entire vehicle, and protects the battery life.

[0031] The predictive dynamic threshold differs from traditional fixed logic thresholds in that it is not a fixed value but rather a function output that changes continuously with the terrain ahead. In this embodiment, the predictive dynamic threshold is calculated based on the average slope of the road ahead, the distance between the vehicle's current position and the slope, and the fixed logic threshold. Data such as the average slope of the road ahead and the vehicle's current position are obtained using electronic horizon data. The specific formula for calculating the predictive dynamic threshold is:

[0032]

[0033] Among them, P' L represents the predictive dynamic threshold, S represents the average slope of the terrain in front of the vehicle's current position, D represents the distance between the vehicle's current position and the slope, and P L Indicates a fixed logic threshold value, A and M are constants, and u is a step function.

[0034] The following describes each parameter.

[0035] Constant M: Represents the distance threshold between the vehicle's current position and the slope. Because the electronic horizon system can predict the slope of the road ahead, a long slope has a negligible impact on the vehicle's energy distribution. Therefore, a constant M is set to indicate that the predictive dynamic logic threshold only begins to change with the terrain ahead when the slope is within M meters (generally 500 meters, but this can be adjusted based on the vehicle's specific conditions. For example, vehicles equipped with large supercapacitors can increase this threshold, while vehicles with smaller supercapacitors can decrease it).

[0036] Step function u: It can be seen that when the actual distance D between the vehicle's current position and the slope is greater than M, the function The value is 0, and the dynamic threshold value of the formula is It means that when the distance between the vehicle's current position and the slope exceeds M, the original default fixed logic threshold value is still used.

[0037] When the distance D between the vehicle's current position and the slope is less than or equal to M, is 1, at this time the predictive dynamic logic threshold value is associated with the slope of the front road section. Because the slope is too large to exceed the limit performance of the vehicle, the energy control can lose its meaning, so the upper limit and lower limit associated with the slope are set, the upper limit is 5 degrees of slope (more than 5 degrees is counted as 5 degrees by default), and the lower limit is -5 degrees of slope (less than -5 degrees of slope is counted as -5 degrees by default). As can be seen from the formula, when the slope of the front road section is 0 (i.e. when the road is flat), that is, when the front ground has no slope, the original default fixed logic threshold value is still used.

[0038] The constant A determines the fluctuation range of the dynamic threshold, which can be set by those skilled in the art according to actual needs, and is preferably set to 0.5 in this embodiment.

[0039] When the slope of the front road section is the upper limit of 5 degrees of slope, that is, when there is a steep uphill in front, the predictive dynamic logic threshold value is 1.5 times the default fixed logic threshold value. The threshold value is increased, which means that more power is output by the battery, and the supercapacitor power is temporarily reserved. When the vehicle runs to a place with a large uphill in front, the vehicle needs higher power output, and the supercapacitor is used to output high power at this time. This can prevent the supercapacitor power from being output too early, and when the vehicle runs to a steep slope and needs high power discharge, the battery has to be used for output. Such passive high power discharge will affect the service life of the battery. Therefore, the calculation formula in this embodiment can dynamically adjust the threshold value according to the uphill in front, reduce the probability of high power discharge of the battery, and protect the battery.

[0040] When the slope of the front road section is the lower limit of -5 degrees of slope, that is, when there is a steep downhill in front, the predictive dynamic logic threshold value is half of the default fixed logic threshold value. The threshold value is reduced, which means that more power is output by the supercapacitor. When the vehicle runs to a place with a large downhill in front, the energy recovered by braking may be more because of the steep downhill, and the supercapacitor has more output power before the slope, so it has more space to recover braking energy and can achieve better energy economy. Since more energy is recovered by the supercapacitor on the downhill road section, this can also prevent the battery from being charged too frequently and affecting the service life of the battery. Therefore, the calculation formula in this embodiment can dynamically adjust the threshold value according to the downhill in front, reduce the energy recovery efficiency, and also protect the battery from frequent charging and discharging.

[0041] Here, the predictive dynamic logic threshold value when the slope in front is taken as the interval boundary value and the advantages it can achieve are illustrated. Obviously, when the slope in front is between (-5, 5), the predictive dynamic logic threshold value also changes reasonably according to the terrain in front.

[0042] The specific process of setting the energy output and recovery ratio of electric vehicle batteries and supercapacitors based on the predictive dynamic threshold value is as follows:

[0043] Based on the current throttle depth and vehicle speed during vehicle driving, the power Pn required for vehicle operation at the current moment is obtained. At the same time, the current battery capacity BSOC and supercapacitor capacity USOC are obtained, and the following judgments are made:

[0044] When Pn<0 and USOC>USOC H When , set the battery power Pb = Pn and the supercapacitor power Pc = 0. This means that the current power demand is negative (energy recovery) and the supercapacitor is fully charged, the lithium battery receives energy for charging.

[0045] When Pn<0 and USOC≤USOC H When , set the battery power Pb = 0 and the supercapacitor power Pc = Pn. This means that when the current power demand is negative (energy recovery) and the supercapacitor is not fully charged, the supercapacitor receives energy for charging.

[0046] When 0≤P n ≤P' L 、USOC>USOC L And BSOC>BSOC L When , set the battery power Pb = Pn and the supercapacitor power Pc = 0. This means that when the current power demand is below the predictive dynamic logic threshold and is positive, and when the battery and supercapacitor SOC levels are both below the protection level where they cannot output power, the vehicle is driven by the battery.

[0047] When P n >P' L 、USOC>USOC L And BSOC>BSOC L When setting the battery power P b =P' L , supercapacitor power P c =P n -P' L Indicates that when the current power demand exceeds the predictive dynamic logic threshold, when the battery and supercapacitor SOC power levels are not at the protection value that cannot be output, the battery will supply the basic power demand P' L , the remaining power P n -P' L Provided by supercapacitors, it drives the vehicle.

[0048] When Pn>0, USOC≤USOC L And BSOC>BSOC LWhen , set the battery power Pb = Pn and the supercapacitor power Pc = 0. This means that when the current power demand is positive and the supercapacitor SOC is low and cannot output power, the battery outputs power.

[0049] When Pn>0, USOC>USOC L And BSOC≤BSOC L When , set the battery power Pb = 0 and the supercapacitor power Pc = Pn. This means that when the current power demand is positive and the battery SOC is low and cannot output power, the supercapacitor outputs power.

[0050] When Pn>0, USOC≤USOC L And BSOC≤BSOC L When the battery power Pb is set to 0 and the supercapacitor power Pc is set to 0, it means that when the battery and supercapacitor SOC are both low and lower than the SOC protection value, no power is output.

[0051] Among them, USOC H and USOC L Respectively represent the upper and lower limits of the supercapacitor SOC power. L Indicates the lower limit of the lithium battery SOC. Since lithium batteries have their own overcharge protection, the upper limit of the lithium battery SOC is not considered here.

[0052] Embodiment 1 of the present invention predicts the terrain ahead based on the electronic horizon system, generates a predictive dynamic logic threshold value according to the electronic horizon information, changes the defect that the conventional fixed logic threshold value does not have predictive optimal energy management, and sets the corresponding energy management strategy according to the predictive dynamic logic threshold value to perform predictive energy management, which can play a positive role in reducing the energy consumption of electric vehicles, preventing battery loss, and improving the economy of vehicles.

[0053] Example 2:

[0054] The present invention also provides an electric vehicle energy management terminal device, comprising a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, the steps in the above-mentioned method embodiment of embodiment 1 of the present invention are implemented.

[0055] Furthermore, as an executable solution, the electric vehicle energy management terminal device can be a computing device such as an onboard computer and a cloud server. The electric vehicle energy management terminal device may include, but is not limited to, a processor and a memory. Those skilled in the art will understand that the above-mentioned component structure of the electric vehicle energy management terminal device is merely an example of an electric vehicle energy management terminal device and does not constitute a limitation on the electric vehicle energy management terminal device. The electric vehicle energy management terminal device may include more or fewer components than those described above, or a combination of certain components, or different components. For example, the electric vehicle energy management terminal device may also include input and output devices, network access devices, buses, etc., which are not limited in the embodiments of the present invention.

[0056] Furthermore, as an executable solution, the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the electric vehicle energy management terminal device, and utilizes various interfaces and lines to connect various parts of the entire electric vehicle energy management terminal device.

[0057] The memory can be used to store the computer programs and / or modules. The processor implements the various functions of the electric vehicle energy management terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application required for a function; the data storage area can store data created based on the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0058] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method in the embodiment of the present invention are implemented.

[0059] If the module / unit integrated in the electric vehicle energy management terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the above-mentioned various method embodiments. Among them, the computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM) and software distribution medium, etc.

[0060] Although the present invention has been particularly shown and described in conjunction with preferred embodiments, it will be understood by those skilled in the art that various changes in form and details may be made to the present invention without departing from the spirit and scope of the invention as defined in the appended claims, and all such changes are within the scope of protection of the present invention.

Claims

1. An electric vehicle energy management method, characterized in that: include: Calculate the predictive dynamic threshold value in real time based on the electronic horizon data, and set the energy output and recovery ratio of the electric vehicle battery and supercapacitor according to the predictive dynamic threshold value; Predictive dynamic threshold P L The calculation formula of ' is: Among them, S represents the average slope of the road ahead of the vehicle's current position, and its upper limit is 5 degrees and the lower limit is -5 degrees. If it is greater than 5 degrees, it defaults to 5 degrees, and if it is less than -5 degrees, it defaults to -5 degrees. D represents the distance between the vehicle's current position and the slope, and P L Indicates a fixed logic threshold value, A and M are constants, M represents the distance threshold between the vehicle's current position and the slope, and u is a step function. When D>M The value of is 0, when D≤M, The value of is 1; The specific process of setting the energy output and recovery ratio of electric vehicle batteries and supercapacitors based on the predictive dynamic threshold value is as follows: Based on the throttle depth and the current vehicle speed, the power Pn required for vehicle operation at the current moment is obtained. At the same time, the current battery capacity BSOC and supercapacitor capacity USOC are obtained, and the following judgments are made: When Pn<0 and USOC>USOC H When , set the battery power Pb = Pn, and the supercapacitor power Pc = 0; When Pn<0 and USOC≤USOC H When setting, set the battery power Pb = 0 and the supercapacitor power Pc = Pn; When 0≤P n ≤P' L 、USOC>USOC L And BSOC>BSOC L When , set the battery power Pb = Pn, and the supercapacitor power Pc = 0; When P n >P' L 、USOC>USOC L And BSOC>BSOC L When setting the battery power P b =P' L , supercapacitor power P c =P n -P' L ; When Pn>0, USOC≤USOC L And BSOC>BSOC L When , set the battery power Pb = Pn, and the supercapacitor power Pc = 0; When Pn>0, USOC>USOC L And BSOC≤BSOC L When setting, set the battery power Pb = 0 and the supercapacitor power Pc = Pn; When Pn>0, USOC≤USOC L And BSOC≤BSOC L When setting, set the battery power Pb = 0 and the super capacitor power Pc = 0; Among them, USOC H and USOC L They represent the upper and lower limits of the supercapacitor SOC, BSOC L Indicates the lower limit of the lithium battery SOC.

2. The electric vehicle energy management method according to claim 1, characterized in that: A is 3. An electric vehicle energy management terminal device, characterized by: The method comprises a processor, a memory, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 2 when executing the computer program.

4. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 2 are implemented.

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