Electric drive assembly efficiency forward optimization method, product, medium and system

Abstract

The invention discloses an electric drive assembly efficiency forward optimization method, a product, a medium and a system. The method comprises the following steps: 1) acquiring working condition data of a vehicle and converting the working condition data into a power demand; 2) according to the power demand of the vehicle, obtaining a thermal distribution diagram of the vehicle wheel end energy consumption demand; 3) assuming a speed reducer speed ratio; 4) performing simulation according to the power demand to obtain the efficiency map of the motor and the electric control; a high-energy-consumption area in the thermal distribution diagram is matched with an efficient interval in the efficiency map, and a preliminary speed reducer speed ratio is obtained; (5) replacing the assumed speed reducer speed ratio with the initial speed reducer speed ratio, carrying out motor and electric control data updating iteration according to the step (4) until the total energy consumption is minimum, and determining a motor and electric control initial scheme; 6, the efficient interval of electric control of the motor and the high-energy-consumption interval of the thermal distribution diagram are matched again in combination with the speed ratio of the speed reducer, and the final scheme is obtained.The method has the advantages that the efficiency of the electric drive assembly is improved, and the energy consumption of the electric drive assembly is reduced.

Description

Technical Field

[0001] The present invention mainly relates to the technical field of new energy vehicles, and particularly relates to a method, product, medium and system for positive optimization of the efficiency of an electric drive assembly. Background Art

[0002] The electric drive assembly of a new energy vehicle includes three main components: a motor, a motor controller, and a reducer. It is an energy conversion device that converts the electrical energy stored in the battery into the mechanical energy required for the wheels to roll, and is used to drive the entire vehicle. There are three main links in the entire energy conversion process: the motor controller converts the direct current of the power battery into three-phase alternating current, the motor converts the three-phase alternating current into rotational mechanical energy, and the reducer increases the torque by reducing the speed for the mechanical energy output by the motor to meet the power requirements of the entire vehicle. There are three efficiency loss links in the entire energy conversion process. The first is the process of converting direct current to alternating current, the second is the process of converting alternating current to mechanical energy, and the third is the process of reducing speed and increasing torque in the gearbox. In order to improve the efficiency of the entire electric drive and reduce the energy consumption of the entire electric assembly, it is necessary to perform positive design matching for the parameters of the motor, motor controller, and reducer, and achieve the global optimum of the electric drive assembly efficiency through the optimization of each parameter.

[0003] In the current industry, there is no clear positive matching optimization design method for the efficiency of the electric drive assembly. Instead, the efficiency reverse calibration method is mostly used for multiple attempts to obtain a high-efficiency solution, which requires a large amount of calculation data and takes a long time.

[0004] Through patent retrieval and other means, the following relevant industry information is obtained: Patent Application: "A Method for Evaluating the Efficiency of an Electric Drive System of an Electric Vehicle" This patent application is a method for evaluating the efficiency of an electric drive system of an electric vehicle. The steps include: First, conduct a bench test on the electric drive system of the electric vehicle to obtain the drive efficiency value and recovery efficiency value of the electric drive system of the electric vehicle in the drive mode and braking mode; Second, make the drive efficiency value and recovery efficiency value of the electric drive system of the electric vehicle tested in step one into a MAP diagram, and divide the MAP diagram into regions; Third, calculate the average efficiency of the regions divided in step two, and calculate the proportion of different regions; Fourth, compare the average efficiency values and region proportion values of different regions, calculate the comprehensive efficiency of the electric drive system, and evaluate the pros and cons of the electric drive system. By dividing the electric drive efficiency MAP into different regions, and considering the speed range and torque range corresponding to the CLTC maximum speed, as well as the speed range and torque range corresponding to the user's common working conditions, the efficiency of the electric drive system is comprehensively evaluated.

[0005] Patent Application: "A Method for Testing and Evaluating the Working Condition Efficiency of an Electric Drive Assembly of an Equivalent Whole Vehicle" This patent application provides a method for testing and evaluating the working condition efficiency of an electric drive assembly equivalent to a complete vehicle, including at least one of the following steps: S1. Prepare before testing and obtain the parameters required for testing; S2. Debug the test bench and set parameters according to the parameters required for testing obtained in step S1; S3. Conduct a working condition efficiency test and collect the test data; S4. Conduct a result and evaluation of the working condition efficiency test based on the test data in step S3. Beneficial effects of the present invention: From the perspective of the design of the electric drive assembly, the working condition efficiency test method can realize the correlation between the output characteristics of the electric drive assembly and the actual working conditions of the complete vehicle, which is beneficial to the R & D process of the performance parameters, control strategies, prototype calibration, etc. of the electric drive assembly.

[0006] Patent Application: "Method, Device, Vehicle and Storage Medium for Energy Consumption Simulation Calculation of Electric Drive System" This patent application calculates the road spectrum mechanical power of a single cycle mileage based on the working condition road spectrum and vehicle parameters, matches the current efficiency / DC power spectrum data corresponding to each working condition point in the working condition road spectrum, performs local area fitting processing on the DC power of each working condition point in the working condition road spectrum to form the efficiency / DC power of the fitting working condition point; uses the road spectrum mechanical power and the efficiency / DC power of the fitting working condition point to calculate the energy consumption and average efficiency, separates the driving and generating working condition points in the working condition spectrum and respectively statistics the driving energy consumption / efficiency, generating energy consumption / efficiency, comprehensive energy consumption / efficiency of driving and generating in a single cycle, and obtains the cumulative energy consumption and battery state of charge; repeats the above calculations until the battery state of charge reaches the lowest; statistics the total cruising range, and calculates the driving energy consumption, generating energy consumption, comprehensive energy consumption per 100 kilometers, and generating efficiency, driving efficiency, comprehensive efficiency by accumulating the energy consumption of multiple cycles.

[0007] From the retrieved patents, the current focus is on the testing methods and data processing for efficiency, but there are no relevant patents on how to perform forward matching design improvement of efficiency from the front end of design. Summary of the Invention

[0008] In view of the technical problems existing in the prior art, the present invention provides a forward optimization method, product, medium and system for electric drive assembly efficiency that reduces electric drive energy consumption and realizes the optimization of electric drive assembly efficiency.

[0009] To solve the above technical problems, the technical solution proposed by the present invention is: A forward optimization method for electric drive assembly efficiency, including the steps of: 1) Obtain the working condition data of the vehicle and convert the working condition data of the vehicle into power requirements; 2) Obtain the thermal distribution map of the vehicle wheel end energy consumption requirements according to the power requirements of the vehicle; 3) Assume the reduction ratio of the reducer; 4) Simulate the efficiency maps of the motor and the electronic control according to the power demand; match the high-energy consumption areas in the thermal distribution map with the high-efficiency intervals in the efficiency map, and obtain the preliminary reduction gear ratio through speed conversion; 5) Replace the assumed reduction gear ratio with the preliminary reduction gear ratio, update and iterate the motor and electronic control data according to step 4) until the total energy consumption is minimized, end the gear ratio iteration, lock the reduction gear ratio, and determine the preliminary scheme of the motor and the electronic control; 6) According to the preliminary scheme of the motor and the electronic control, match the high-efficiency intervals of the motor and the electronic control with the high-energy consumption intervals of the thermal distribution map again in combination with the reduction gear ratio to obtain the final scheme.

[0010] Preferably, in step 1), the working condition data includes the load spectrum and the peak demand of the electric drive assembly; the load spectrum includes three parameters: time, the required speed of the electric drive assembly, and the required torque of the electric drive assembly; the peak demand of the electric drive assembly includes peak torque, peak speed, and peak power.

[0011] Preferably, the specific process of step 1) is as follows: 1.1) Take the absolute value of all torques and convert them into integers; 1.2) For the working condition data processed in step 1.1), calculate the current power demand through speed and torque.

[0012] Preferably, the specific process of step 2) is as follows: 2.1) Set the step sizes of speed and torque; 2.2) According to the original value ranges of speed and torque, draw a table of speed and torque based on the step sizes of speed and torque; 2.3) For the speed, torque, and power data, find the corresponding grid points in the torque table according to the values of speed and torque, then add the power values to the grid, and accumulate the data in each grid in turn. Finally, the data in each grid is obtained, which is the sum of the power of all working conditions in this grid; the sum of the power in each grid is equivalent to the sum of energy consumption. Highlight the colors of each energy consumption according to the values to obtain the thermal distribution map of the wheel end energy consumption demand.

[0013] Preferably, in step 2), according to the highlighted area of the thermal map of energy consumption demand, obtain the area of energy consumption demand, which is the area that the electric drive assembly needs to focus on for optimization.

[0014] Preferably, in step 4), the interpolation calculation method is simultaneously used to obtain the energy consumption of each working condition point, and the final total energy consumption of the entire working condition is obtained through data accumulation.

[0015] Preferably, in step 6), re-match the core specifications, pole-slot combinations, permanent magnets, and module currents.

[0016] The present invention also discloses a computer program product, including a computer program which, when run by a processor, executes the steps of the method described above.

[0017] The present invention further discloses a computer-readable storage medium, on which a computer program is stored, and the computer program, when run by a processor, executes the steps of the method described above.

[0018] The present invention also discloses a forward optimization system for the efficiency of an electric drive assembly, including a memory and a processor connected to each other. A computer program is stored on the memory, and the computer program, when run by the processor, executes the steps of the method described above.

[0019] Compared with the prior art, the advantages of the present invention are as follows: By converting the operating point into equivalent energy consumption and using the energy consumption heat map to quickly locate the efficiency optimization interval of the electric drive assembly; according to the energy consumption heat map, iterating on the reduction gear ratio to achieve the optimized matching of the electric drive assembly efficiency; according to the reduction gear ratio and the energy consumption heat map, inversely and finely adjusting the motor and electronic control parameters to further improve the efficiency of the electric drive assembly and reduce the energy consumption of the electric drive assembly.

[0020] The present invention calculates the energy consumption according to the operating conditions of the electric drive and can obtain the energy consumption heat distribution map. According to the highlighted area of the energy consumption heat map, the efficiency optimization interval of the operating conditions can be quickly located. By combining the operating condition efficiency of the motor and the electronic control, the first-round rough optimization design matching is obtained by adjusting the reduction gear ratio. Finally, the highest efficiency of the electric drive assembly is obtained by optimizing the parameters of the motor and the electronic control, reducing the energy consumption of the electric drive assembly under the operating conditions, and realizing the forward optimization design of the electric drive assembly.

[0021] The present invention calculates the energy consumption of each operating point through the electric drive operating condition data, and then obtains the energy consumption distribution heat map of the entire operating condition based on data statistical analysis, and finds the high energy consumption distribution area in the operating condition. Through the high energy consumption distribution area, the operating condition interval with the largest energy consumption of the electric drive assembly in the operating condition can be determined, and the efficiency of the entire electric drive assembly can be improved and the energy consumption can be reduced by focusing on the efficiency optimization of this interval.

[0022] The present invention determines the parameters of the reduction gear, the motor and the electronic control in the drive assembly according to the efficiency optimization operating conditions; determines the efficiency optimization operating condition interval according to the high energy consumption interval. In the first round, the rough matching of the high-efficiency intervals of the motor and the electronic control is realized through the reduction gear ratio matching. In the second round, the fine matching is carried out by adjusting the parameters of the motor and the electronic control; through two rounds of efficiency matching design, the electric drive energy consumption is reduced and the best optimization of the electric drive assembly efficiency is realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is the original operating condition data diagram of the present invention.

[0024] Figure 2 This is the graph of the operating condition data after being made positive in the present invention.

[0025] Figure 3 This is the graph of the required power of the operating condition in the present invention.

[0026] Figure 4 This is the speed-torque grid graph in the present invention.

[0027] Figure 5 This is the heat map of the wheel-end energy consumption requirement in the present invention.

[0028] Figure 6 This is the efficiency map of the motor and its electronic control in the present invention.

[0029] Figure 7 This is the distribution graph of the operating condition points in the present invention.

[0030] Figure 8 This is the refined matching graph of efficiency in the present invention.

[0031] Figure 9 This is the flowchart of the forward optimization method for the efficiency of the electric drive assembly in the present invention in the embodiment. Detailed implementation manners

[0032] The present invention will be further described below in conjunction with the accompanying drawings of the specification and specific embodiments.

[0033] As Figure 9 shown, the forward optimization method for the efficiency of the electric drive assembly provided by the embodiment of the present invention specifically includes the following steps: 1) Conversion of operating condition data into power For the forward optimization design of the efficiency of the electric drive assembly for new energy vehicles, it is necessary to convert it into power demand based on the relevant operating condition load spectrum provided by the customer (the load spectrum includes three parameters: time, required speed of the electric drive assembly, and required torque of the electric drive assembly, as Figure 1 shown) and the peak demand of the electric drive assembly (including peak torque, peak speed, and peak power, assumed to be torque_peak, speed_peak, and power_peak respectively). The specific process is as follows: 1.1) The torque of the operating condition data usually has negative values. In order to facilitate subsequent data processing and analysis, it is necessary to take the absolute value of all torques and convert them into integers, as Figure 2 shown; After taking the absolute value of the operating condition data, there is a maximum value for both the speed and torque data, assumed to be defined as speed_max and torque_max respectively; there is a minimum value for both the speed and torque data, assumed to be defined as speed_min and torque_min respectively; 1.2) For the working condition load data, the current power demand can be calculated through the rotational speed and torque, and the results are as Figure 3 shown.

[0034] 2) Complete the conversion of the thermal distribution map according to the power At this stage, the key is to map and convert the power data to the rotational speed-torque working condition points. The specific process is as follows: 2.1) Set the step sizes of the rotational speed and torque according to engineering experience, assumed to be speed_step and torque_step respectively; 2.2) According to the original value ranges of the rotational speed and torque, and based on the step sizes of the rotational speed and torque, draw grids of the rotational speed and torque, as Figure 4 shown.

[0035] 2.3) For the Figure 2 rotational speed and torque, and the Figure 3 power data in, find the corresponding grid points according to the values of the rotational speed and torque in the Figure 4 , then add the corresponding power value in the Figure 3 to this grid. The data in each grid is accumulated in sequence, and finally the data in each grid is obtained, which is the sum of the power of all working condition points in this grid. Since the time of the working condition data is at equal step sizes, the sum of the power in each grid can be equivalent to the sum of the energy consumption. Highlight the colors of each energy consumption according to the values, and obtain the thermal distribution map of the wheel end energy consumption demand, specifically as Figure 5 shown.

[0036] According to the highlighted area of the thermal map of the energy consumption demand, the area of the energy consumption demand can be obtained, as shown by the red square area in Figure 5 . This area is the key optimization area that the electric drive assembly needs to focus on.

[0037] 3) Initially assume the reduction ratio of the reducer According to the actual situation of the industry and the company, initially determine a reduction ratio of the reducer, assumed to be i0, as the initial value for subsequent optimization of the reduction ratio.

[0038] 4) Initially determine the reduction ratio of the reducer According to the requirements, the peak torque demand of the motor is torque_max / i0, and the peak rotational speed of the motor is speed_max*i0. Combining with the selection of the electric control module, the efficiency map of the motor and the electric control can be obtained through simulation, as Figure 6 shown.

[0039] In order to improve the efficiency of the electric drive assembly, it is necessary to make the Figure 5 high-energy consumption area in the thermal distribution map coincide with the Figure 6Match the high-efficiency range in the efficiency map. Through speed conversion, the speed ratio can be initially locked. Assume that the determined speed ratio is i0_need (According to the data in the above figure, the speed corresponding to the maximum energy consumption demand at the wheel end is 450 rpm. Combining with Figure 6 's efficiency map, the point with the highest efficiency can be obtained near 6000 rpm, and the speed ratio is initially locked at 13.3). Combine the points in Figure 2 with Figure 6 to obtain the distribution of the operating points of the electric drive assembly in the efficiency map, as shown in Figure 7 ; At the same time, use the interpolation calculation method to obtain the energy consumption of each operating point, and accumulate the data to obtain the final total energy consumption of the entire operating condition.

[0040] 5) Lock the speed ratio of the reducer Replace the initially set speed ratio i0 of the reducer with the initially locked speed ratio above, and re-update and iterate the motor and electronic control data according to step 4) until the total energy consumption is minimized, end the speed ratio iteration, lock the speed ratio of the reducer, and at the same time determine the preliminary schemes of the motor and electronic control.

[0041] 6) Lock the motor and electronic control scheme According to the above preliminary schemes of the motor and electronic control, re-match for the core specifications, pole-slot combination, permanent magnet, module current, etc. Combine the locked speed ratio to refine the matching between the high-efficiency range of the motor and electronic control and the Figure 5 high-energy consumption range to further reduce the total energy consumption, and then obtain the final motor and electronic control scheme, as shown in Figure 8 .

[0042] The present invention converts the operating points into equivalent energy consumption and uses the energy consumption heat map to quickly locate the efficiency optimization range of the electric drive assembly; according to the energy consumption heat map, iterate for the speed ratio of the reducer to achieve the optimized matching of the efficiency of the electric drive assembly; according to the speed ratio of the reducer and the energy consumption heat map, perform refined adjustment of the motor and electronic control parameters in reverse to further improve the efficiency of the electric drive assembly and reduce the energy consumption of the electric drive assembly.

[0043] The present invention calculates the energy consumption according to the operating conditions of the electric drive and can obtain the energy consumption heat distribution map. According to the highlighted area of the energy consumption heat map, the efficiency optimization range of the operating conditions can be quickly located. Through combining the operating efficiency of the motor and electronic control, the first-round rough optimization design matching is obtained by adjusting the speed ratio of the reducer. Finally, the highest efficiency of the electric drive assembly is obtained by optimizing the parameters of the motor and electronic control, reducing the energy consumption of the electric drive assembly operating conditions, and realizing the positive optimization design of the electric drive assembly.

[0044] The present invention calculates the energy consumption of each operating point through the electric drive operating condition data, and then obtains the energy consumption distribution heat map of the entire operating condition based on data statistical analysis to find the high-energy consumption distribution area in the operating condition. Through the high-energy consumption distribution area, the operating condition interval with the largest energy consumption of the electric drive assembly in the operating condition can be determined, and the efficiency optimization is focused on this interval to improve the operating condition efficiency of the entire electric drive assembly and reduce the energy consumption.

[0045] The present invention determines the parameters of the reducer, motor, and electronic control in the drive assembly according to the efficiency optimization operating condition; determines the efficiency optimization operating condition interval according to the high-energy consumption interval. In the first round, the rough matching of the high-efficiency intervals of the motor and the electronic control is realized through the reduction ratio matching of the reducer, and in the second round, the refined matching is carried out by adjusting the parameters of the motor and the electronic control; through the two-round efficiency matching design, the electric drive energy consumption is reduced to achieve the best optimization of the electric drive assembly efficiency.

[0046] The present invention also discloses a computer program product, including a computer program, and the steps of the above-mentioned method are executed when the computer program is run by a processor. The present invention further discloses a computer-readable storage medium, on which a computer program is stored, and the steps of the above-mentioned method are executed when the computer program is run by a processor. The present invention also discloses a forward optimization system for the efficiency of an electric drive assembly, including a memory and a processor connected to each other, a computer program is stored on the memory, and the steps of the above-mentioned method are executed when the computer program is run by the processor. The products, media, and systems of the present invention, corresponding to the above-mentioned method, also have the advantages as described in the above-mentioned method.

[0047] All or part of the processes in the above-described embodiment methods of the present invention can also be completed by hardware related to computer program instructions. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable storage medium includes: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc. The memory is used to store the computer program and / or module. The processor realizes various functions by running or executing the computer program and / or module stored in the memory, and by calling the data stored in the memory. The memory can include high-speed random access memory, and can also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one magnetic disk storage device, flash device, or other volatile solid-state storage devices, etc.

[0048] The above are only the preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions falling within the idea of the present invention belong to the protection scope of the present invention. It should be pointed out that for those of ordinary skill in the art, several improvements and refinements made without departing from the principle of the present invention should be regarded as within the protection scope of the present invention.

Claims

1. A method for forward optimization of electric drive assembly efficiency, characterized in that: Includes steps: 1) Obtain the vehicle's operating data and convert it into success rate requirements; 2) Obtain the thermal distribution diagram of the vehicle's wheel-end energy consumption demand based on the vehicle's power demand; 3) Assume the reducer speed ratio; 4) Get the efficiency map of the motor and electronic control based on the power demand simulation; Match the high energy consumption area in the thermal distribution map with the high efficiency range in the efficiency map, and obtain the preliminary reducer speed ratio through speed conversion; 5) Replace the assumed reducer speed ratio with the preliminary reducer speed ratio, and iterate the motor and electronic control data according to step 4) until the total energy consumption is minimized. End the speed ratio iteration, lock the reducer speed ratio, and determine the preliminary plan for the motor and electronic control; 6) Based on the preliminary plan of the motor and electronic control, the high-efficiency range of the motor and electronic control is re-matched with the high-energy consumption range of the thermal distribution diagram in combination with the speed ratio of the reducer to obtain the final plan.

2. The method for forward optimization of electric drive assembly efficiency according to claim 1, characterized in that: In step 1), the operating condition data includes a load spectrum and an electric drive assembly peak demand; the load spectrum includes three parameters: time, electric drive assembly required speed, and electric drive assembly required torque; the electric drive assembly peak demand includes peak torque, peak speed, and peak power.

3. The method for forward optimization of electric drive assembly efficiency according to claim 2, characterized in that: The specific process in step 1) is: 1.1) Convert all absolute values ​​of torque into integers; 1.2) Based on the operating data processed in step 1.1), the current power demand is calculated through the speed and torque.

4. The method for forward optimization of electric drive assembly efficiency according to claim 1, 2 or 3, characterized in that: The specific process of step 2) is as follows: 2.1) Set the speed and torque step size; 2.2) Draw a table of speed and torque based on the original speed and torque ranges and speed and torque steps; 2.3) For the speed, torque and power data, find the corresponding grid point in the torque table according to the speed and torque values, then add the power value to the grid, accumulate the data in each grid in turn, and finally get the data in each grid, which is the sum of the power of all operating points in this grid; the sum of the power in each grid is equivalent to the sum of the energy consumption, and each energy consumption is highlighted in color according to the value to obtain the thermal distribution diagram of the wheel-end energy consumption demand.

5. The method for forward optimization of electric drive assembly efficiency according to claim 4, characterized in that: In step 2), the energy demand area is obtained based on the highlighted area of ​​the energy demand heat map. This area is the area where the electric drive assembly needs to be optimized.

6. The method for forward optimization of electric drive assembly efficiency according to claim 4, characterized in that: In step 4), the interpolation calculation method is used to obtain the energy consumption of each operating point, and the final total energy consumption of the entire operating condition is obtained by accumulating the data.

7. The method for forward optimization of electric drive assembly efficiency according to claim 1, 2 or 3, characterized in that: In step 6), the core specifications, pole slot matching, permanent magnets, and module current are re-matched.

8. A computer program product, comprising 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 7 are performed.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the computer program performs the steps of the method according to any one of claims 1 to 7.

10. An electric drive assembly efficiency forward optimization system, comprising a memory and a processor connected to each other, wherein a computer program is stored in the memory, characterized in that: When the computer program is executed by a processor, the computer program performs the steps of the method according to any one of claims 1 to 7.

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