Vehicle energy flow analysis method and device based on technical rack, equipment and medium

Abstract

The invention discloses a vehicle energy flow analysis method, device and equipment based on a technical rack and a medium, and relates to the technical field of vehicles, and the method comprises the steps that processing equipment obtains test conditions, the test conditions comprise a test mode and the simulation opening degree of an accelerator pedal, according to the test mode and the simulation opening degree, target voltage input to a vehicle control unit VCU is determined, and the target voltage is input to the vehicle control unit VCU; the target voltage is converted into analog voltage through a digital-to-analog conversion module, the analog voltage is output to the VCU, so that the VCU controls the motor according to the analog voltage, and in the process that the VCU controls the motor to operate according to the analog voltage, vehicle energy data is collected, and vehicle energy flow is analyzed according to the vehicle energy data. The method can improve the accuracy of vehicle energy flow analysis.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a vehicle energy flow analysis method, device, equipment and medium based on a technical bench. Background Art

[0002] In the field of vehicle analysis, vehicle energy flow analysis based on technical test benches is an important testing method, which helps to fully understand the energy consumption distribution of the vehicle under different operating conditions, thereby providing effective guidance for optimizing the matching of components, improving the operating efficiency of each component, and selecting and designing each component.

[0003] At present, when testing the electric drive efficiency under different conditions on the technical bench, the driver can control the opening of the accelerator pedal with his feet. However, since the vehicle will shake during the test, the manual control of the accelerator pedal has poor stability. Therefore, the data obtained in this case will have large errors, which will lead to poor accuracy in vehicle energy flow analysis. Summary of the invention

[0004] The present application provides a vehicle energy flow analysis method, device, equipment and medium based on a technical bench, which can improve the accuracy of vehicle energy flow analysis.

[0005] In order to achieve the above purpose, this application adopts the following technical solutions: In a first aspect, the present application provides a vehicle energy flow analysis method based on a technical bench, the method comprising: Acquiring test conditions, wherein the test conditions include a test mode and a simulated opening of an accelerator pedal; Determining a target voltage input to a vehicle control unit VCU according to the test mode and the simulated opening; The target voltage is converted into an analog voltage by a digital-to-analog conversion module, and outputted to the VCU, so that the VCU controls the motor according to the analog voltage; collecting vehicle energy data during the process in which the VCU controls the operation of the motor according to the simulated voltage; The vehicle energy flow is analyzed based on the vehicle energy data.

[0006] In some possible implementations, obtaining the test condition includes: Presenting a test interface to a user, the test interface comprising a first configuration area for a test mode and a second configuration area for a simulated opening of an accelerator pedal; The test mode configured by the user in the first configuration area and the simulated opening of the accelerator pedal configured in the second configuration area are obtained.

[0007] In some possible implementations, the accelerator pedal includes a first positive output terminal, a first negative output terminal, a second positive output terminal, and a second negative output terminal, the VCU includes a first positive input terminal, a first negative input terminal, a second positive input terminal, and a second negative input terminal, and the digital-to-analog conversion module includes a third positive output terminal and a fourth positive output terminal; The first positive output terminal is disconnected from the first positive input terminal, the second positive output terminal is disconnected from the second positive input terminal, the third positive output terminal is connected to the first positive input terminal, the fourth positive output terminal is connected to the second positive input terminal, the first negative output terminal is connected to the first negative input terminal, and the second negative output terminal is connected to the second negative input terminal.

[0008] In some possible implementations, after collecting the vehicle energy data, the method further includes: Generating multiple groups of sample index data and multiple groups of sample energy consumption data according to the vehicle energy data; Determine the correlation between the sample indicator data and the sample energy consumption data; The sample indicator data with correlation lower than the correlation threshold are removed from the multiple groups of sample indicator data to obtain remaining sample indicator data and remaining sample energy consumption data; The remaining sample index data and the remaining sample energy consumption data are used to train a vehicle energy consumption prediction model.

[0009] In some possible implementations, determining the correlation between the sample indicator data and the sample energy consumption data includes: in, is the correlation between the i-th sample index data and the i-th sample energy consumption data, is the set of the i-th indicator data, is the set of energy consumption data of the i-th vehicle, for The j-th sample indicator variable in for The j-th sample energy consumption variable in for 、 The joint probability density of for The marginal probability density of for The marginal probability density of , and The product of is equal to or The number of variables in a is the horizontal axis coordinate variable of the grid G,b is the vertical axis coordinate variable of the grid G, and are all positive integers, , q is or The number of variables in , j is a positive integer, j is less than or equal to q.

[0010] In some possible implementations, the method further includes: Obtain the indicator data to be predicted; The index data to be predicted is input into the vehicle energy consumption prediction model to obtain the vehicle energy consumption corresponding to the index data to be predicted.

[0011] In some possible implementations, the method further includes: Present the analysis results to the user.

[0012] In a second aspect, the present application provides a vehicle energy flow analysis device based on a technical bench, the device comprising: An acquisition module, used for acquiring test conditions, wherein the test conditions include a test mode and a simulated opening of an accelerator pedal; a determination module, configured to determine a target voltage to be input to a vehicle control unit VCU according to the test mode and the simulated opening; convert the target voltage into an analog voltage through a digital-to-analog conversion module, and output the analog voltage to the VCU, so that the VCU controls the motor according to the analog voltage; A collection module, used for collecting vehicle energy data when the VCU controls the motor operation according to the analog voltage; An analysis module is used to analyze the vehicle energy flow according to the vehicle energy data.

[0013] In a third aspect, the present application provides a computing device, including a memory and a processor; One or more computer programs are stored in the memory, and the one or more computer programs include instructions; when the instructions are executed by the processor, the computing device executes the method as described in any one of the first aspects.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium is used to store a computer program, and the computer program is used to execute the method as described in any one of the first aspects.

[0015] It can be seen from the above technical solution that the present application has at least the following beneficial effects: In the present application, the processing device obtains the test conditions, which include the test mode and the simulated opening of the accelerator pedal. According to the test mode and the simulated opening, the target voltage input to the vehicle control unit VCU is determined, and the target voltage is converted into an analog voltage through the digital-to-analog conversion module, and output to the VCU, so that the VCU controls the motor according to the analog voltage. During the process of VCU controlling the motor according to the analog voltage, the vehicle energy data is collected, and the vehicle energy flow is analyzed according to the vehicle energy data. At present, when testing the electric drive efficiency under different conditions on the technical bench, the opening of the accelerator pedal can be controlled by the driver with his feet. Since the vehicle will shake during the test, the stability of the manual control of the accelerator pedal is poor. Therefore, in this case, the data obtained by the test will have a large error, which will lead to poor accuracy in the vehicle energy flow analysis. It can be seen that the scheme of the present application can improve the accuracy of the vehicle energy flow analysis.

[0016] It should be understood that the description of technical features, technical solutions, beneficial effects or similar language in this application does not imply that all features and advantages can be realized in any single embodiment. On the contrary, it is understood that the description of features or beneficial effects means that specific technical features, technical solutions or beneficial effects are included in at least one embodiment. Therefore, the description of technical features, technical solutions or beneficial effects in this specification does not necessarily refer to the same embodiment. Furthermore, the technical features, technical solutions and beneficial effects described in the present embodiment can also be combined in any appropriate manner. Those skilled in the art will understand that the embodiment can be realized without one or more specific technical features, technical solutions or beneficial effects of a specific embodiment. In other embodiments, additional technical features and beneficial effects can also be identified in a specific embodiment that does not embody all embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flow chart of a vehicle energy flow analysis method based on a technical bench provided in an embodiment of the present application; Figure 2 A schematic diagram of a test interface provided in an embodiment of the present application; Figure 3 A schematic diagram of a vehicle testing process provided in an embodiment of the present application; Figure 4 A schematic diagram of a method for testing vehicle data provided in an embodiment of the present application; Figure 5 A schematic diagram of a vehicle energy consumption prediction model provided in an embodiment of the present application; Figure 6 A flow chart of a vehicle data management system provided in an embodiment of the present application; Figure 7A schematic diagram of a vehicle energy flow analysis device based on a technical bench provided in an embodiment of the present application; Figure 8 A schematic diagram of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] The terms "first", "second", "third", etc. in the specification of this application and the accompanying drawings are used to distinguish different objects rather than to limit a specific order.

[0019] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0020] At present, when testing the electric drive efficiency under different conditions on the technical bench, the driver can control the opening of the accelerator pedal with his feet. However, due to the vibration of the vehicle during the test, the manual control of the accelerator pedal has poor stability. Therefore, the data obtained in this case will have a large error, which will lead to poor accuracy in vehicle energy flow analysis. Another solution is to control the opening of the accelerator pedal through a pedal robot, which is not only cumbersome and time-consuming to install, but also relatively expensive.

[0021] In view of this, an embodiment of the present application provides a vehicle energy flow analysis method based on a technical test bench, in which a processing device obtains test conditions, and the test conditions include a test mode and a simulated opening of an accelerator pedal. According to the test mode and the simulated opening, a target voltage input to a vehicle control unit VCU is determined, and the target voltage is converted into an analog voltage through a digital-to-analog conversion module, and output to the VCU, so that the VCU controls the motor according to the analog voltage. In the process of VCU controlling the motor according to the analog voltage, vehicle energy data is collected, and the vehicle energy flow is analyzed based on the vehicle energy data.

[0022] In order to make the technical solution of the present application clearer and easier to understand, a vehicle energy flow analysis method based on a technical bench provided in an embodiment of the present application is introduced. Figure 1 As shown, the figure is a flow chart of a vehicle energy flow analysis method based on a technical bench provided in an embodiment of the present application. The vehicle energy flow analysis method can be executed by a processing device, and the method includes: S101. A processing device obtains test conditions.

[0023] A processing device is a hardware system or software system used to perform specific tasks or process data. In scenarios involving vehicle energy flow analysis, a processing device may refer to a computer, server, or specific software platform dedicated to calculating, simulating, or analyzing vehicle energy flow.

[0024] The test conditions include the test mode and the simulated opening of the accelerator pedal. The test modes include sports mode, comfort mode and snow mode. The test interface is as follows: Figure 2 As shown in the figure, this figure is a schematic diagram of a test interface provided by an embodiment of the present application. It can be seen in the figure that the test interface includes a first configuration area 301 for the test mode, a second configuration area 302 for the simulated opening of the accelerator pedal, and a submission control 303. The user can configure the test mode in the first configuration area 301 and the simulated opening of the accelerator pedal in the second configuration area 302. After the user completes the above configuration, the submission control 303 can be triggered, and then the processing device can obtain the content configured by the user in the first configuration area 301 and the second configuration area 302 based on the trigger operation.

[0025] S102: The processing device determines a target voltage to be input to the vehicle control unit VCU according to the test mode and the simulated opening.

[0026] In different test modes, the mapping relationship between the opening of the accelerator pedal and the voltage input to the VCU is different. For example, when the test mode is the sports mode, the mapping relationship between the opening of the accelerator pedal and the voltage input to the VCU is a first mapping relationship, and when the test mode is the energy-saving mode, the mapping relationship between the opening of the accelerator pedal and the voltage input to the VCU is a second mapping relationship.

[0027] It should be noted that the above mapping relationship is obtained by fitting based on measured data in advance.

[0028] After the processing device determines the test mode of this time, it can obtain the mapping relationship corresponding to the test mode based on the test mode. Then the processing device brings the simulated opening configured by the user into the above mapping relationship to obtain the corresponding target voltage, thereby determining the target voltage input to the vehicle control unit VCU.

[0029] S103: The processing device converts the target voltage into an analog voltage through a digital-to-analog conversion module, and outputs the analog voltage to the VCU.

[0030] The processing device disconnects the 2-way hard-wire connection between the accelerator pedal and the VCU, connects the 2-way output voltage of the digital-to-analog conversion module to the VCU input harness, and then controls the digital-to-analog conversion module to convert the target voltage into analog voltage through the test interface of the host computer, thereby achieving precise control of vehicle acceleration. The principle diagram of the above process is shown in Figure 3As shown, the figure is a schematic diagram of a vehicle test process provided by an embodiment of the present application. The figure includes an accelerator pedal 401, a VCU 402, a digital-to-analog conversion module 403, a host computer 404 and a power supply module 405, wherein the power supply module 405 is used to provide a power supply voltage to the digital-to-analog conversion module 403, and the power supply voltage can be 12V.

[0031] Among them, the accelerator pedal 401 includes a first positive output terminal 411, a first negative output terminal 412, a second positive output terminal 413 and a second negative output terminal 414, the VCU 402 includes a first positive input terminal 415, a first negative input terminal 416, a second positive input terminal 417 and a second negative input terminal 418, and the digital-to-analog conversion module includes a third positive output terminal 419 and a fourth positive output terminal 420.

[0032] The first positive output terminal 411 is disconnected from the first positive input terminal 415, the second positive output terminal 413 is disconnected from the second positive input terminal 417, the third positive output terminal 419 is connected to the first positive input terminal 411, the fourth positive output terminal 420 is connected to the second positive input terminal 417, the first negative output terminal 412 is connected to the first negative input terminal 416, and the second negative output terminal 414 is connected to the second negative input terminal 418.

[0033] Setting up two groups of ports can ensure stable signal transmission and form redundant backup to improve reliability. When one group of ports fails, the voltage signal output by the accelerator pedal can still be transmitted to the VCU through the other group of ports to determine the maneuverability of the vehicle.

[0034] S104. While the VCU controls the operation of the motor according to the analog voltage, the vehicle energy data is collected.

[0035] In this application, before the processing device obtains the data to be processed, high-voltage architecture research and sensor layout are required. First, the vehicle high-voltage system architecture and low-voltage main electrical components are determined, and the sensor layout scheme is determined, such as Figure 4 As shown, the figure is a schematic diagram of a method for testing vehicle data provided by an embodiment of the present application. In the figure, the vehicle architecture includes a transmission system architecture 201, a high-voltage component architecture 202, a low-voltage component architecture 203 and a CAN communication architecture 204. The sensor arrangement includes the arrangement of a current sensor 211, a voltage sensor 212, a temperature sensor 213, a pressure sensor 214, a flow sensor 215, a torque sensor 216 and a CAN communication interface 217. The purpose of arranging the current sensor and the voltage sensor is to calculate the power. However, some signals are difficult to obtain through the sensor arrangement, so it is necessary to use a signal analysis method to obtain information such as battery SOC, battery minimum temperature, battery maximum temperature, battery cell voltage, motor torque, motor speed, compressor speed, etc.

[0036] Specifically, the deployment locations of voltage sensors include the interfaces of high-voltage electrical components and low-voltage electrical components. Since high-voltage wires cannot be damaged, otherwise it will cause danger. Therefore, a set of test harnesses is customized according to the model of the electrical interface of the high-voltage component. The test harness can be connected in series to the high-voltage harness. The test harness includes a voltage sensor and a signal output harness. After the test harness is installed, the signal output line is connected to the data acquisition module.

[0037] The current sensor deployment locations generally include high-voltage components and low-voltage components. High-voltage components include power batteries, front electric drive modules, rear electric drive modules, high-voltage PTC (Positive Temperature Coefficient), air conditioning compressors, DCDC input terminals, etc. Low-voltage components include DCDC output terminals, cooling fans, motor water pumps, battery water pumps, air conditioning water pumps, blowers, 12V batteries, etc. Since different components have different rated powers, when selecting the current sensor range, ensure that the sensor range does not exceed 1.5 times the maximum current of the high-voltage and low-voltage components.

[0038] The temperature sensor deployment locations mainly include the battery water inlet and outlet, motor water inlet and outlet, radiator water inlet and outlet, heat exchanger water inlet and outlet and other major heat-generating and heat-dissipating components, which are used to assist in analyzing the correlation between passenger compartment energy consumption, battery energy consumption and temperature.

[0039] Flow sensors are mainly arranged in the motor cooling circuit water pipes, battery cooling circuit water pipes, air conditioning circuit water pipes, and radiator water pipes. Combined with temperature sensors, they are used to analyze the heat dissipation and heat generation of different power components.

[0040] The CAN communication interface obtains CAN signals through the twisted pair cables on the connectors of key controllers such as the battery management system and battery controller, creates specific working conditions to identify data that changes with the working condition characteristics, and then calibrates the offset and proportional values ​​with sensors, external devices and other instruments. For example, when analyzing the battery SOC, DC fast charging conditions are carried out, the CAN data change trend is determined, the signal ID and bytes are determined, and then the CAN data is calibrated according to the instrument values ​​and charging pile values.

[0041] The following are tests on the vehicle bench, including the range test 221, charging performance test 222, resistance decomposition test 223 and electric drive efficiency test 224 under different temperature conditions. The range test 221 includes testing of the vehicle at high temperature, low temperature, ultra-low temperature, and normal temperature. The charging performance test 222 includes testing of normal temperature, high temperature, low temperature, and ultra-low temperature. The resistance decomposition test 223 includes mechanical resistance of the transmission system, caliper resistance, bearing resistance and other resistances at different temperatures and vehicle speeds. The electric drive efficiency test 224 mainly includes the electric drive efficiency at different temperatures, such as normal temperature and low temperature conditions. Sensor data and CAN bus data are collected synchronously during the test.

[0042] Specifically, the cruising range test 221 uses the test matrix in Table 1, and all sensor data and CAN bus data are recorded during the test.

[0043] Table 1: The charging performance test 222 uses the following test matrix. Considering that the air conditioner may be turned on for charging during the actual charging process, the constructed test matrix is ​​closer to the actual needs. All sensor data and CAN bus data are recorded during the test.

[0044] Table 2: The resistance decomposition test 223 includes a road sliding resistance test, a drum drag test, and a four-motor bench test. The road sliding resistance test can test all the resistances encountered by the vehicle, including wind resistance, rolling resistance, and mechanical internal resistance; the drum drag test can test all resistances except air resistance, and the four-motor bench test can test mechanical internal resistance. Remove the tires of the vehicle and install it on a four-motor test bench. Power on the vehicle, put it in neutral, and then fully warm up the vehicle, such as towing the vehicle in reverse at 80km / h for 40 minutes. After fully warming up the vehicle, conduct formal tests. The test speeds are 10km / h, 20km / h, 30km / h... the highest speed. Each speed point is stable for half a minute. Complete 3 groups of tests in succession, and calculate the average value to obtain the vehicle's mechanical resistance T1 at each speed point. Then remove the drive half-shaft. Similarly, fully warm up the vehicle. Test the speed and method as above to obtain the resistance T2 of the caliper and the bearing. Then remove the caliper and conduct a test using the same method as above to obtain the bearing resistance T3. Then calculate the bearing resistance based on T2 and T3.

[0045] The electric drive efficiency test 224 requires the collection of the electric drive input current, voltage, wheel-end speed and torque. Because there are many test points, only the efficiency map under normal temperature conditions is tested. The test bench is a four-motor bench, and the test vehicle speed is 10km / h, 20km / h, 30km / h... the maximum vehicle speed.

[0046] The test index calculation includes a cruising range index 231 , a charging performance index 232 , a resistance index 233 and an efficiency map index 234 .

[0047] The processing equipment collects the test data obtained during the test process through the data acquisition equipment in order to conduct subsequent energy flow analysis.

[0048] S105: Analyze the vehicle energy flow according to the vehicle energy data.

[0049] Energy flow analysis includes calculating the energy consumed by high-voltage and low-voltage components in charging tests and range tests, and calculating the transmission efficiency of the electric drive system in efficiency tests.

[0050] Specifically, the range test calculates the range, power consumption per 100 kilometers, range reduction rate, instrument range estimation accuracy, high and low voltage component energy consumption, and heat generation and heat dissipation of each component. The charging test calculates the charging time, charging power, average charging power, low temperature charging time increase rate, high and low voltage component energy consumption, and heat generation and heat dissipation of each component. The resistance decomposition test calculates the vehicle resistance, transmission system resistance, caliper resistance, and bearing resistance at each vehicle speed.

[0051] Specifically, the energy consumption of high- and low-voltage components in the range test includes battery discharge, power consumption of the front electric drive system, power consumption of the rear electric drive system, compressors, PTC, DCDC and other high-voltage components, power consumption of the low-voltage end of DCDC, fans, blowers, battery water pumps and other low-voltage components. The energy consumption of high- and low-voltage components in the charging test includes battery charge, power consumption of the front electric drive system, power consumption of the rear electric drive system, compressors, PTC, DCDC and other high-voltage components, power consumption of the low-voltage end of DCDC, fans, blowers, battery water pumps and other low-voltage components.

[0052] The following is a calculation of the power consumption of high-voltage and low-voltage components in electric vehicles: in, The power consumption of high-voltage components in electric vehicles. is the voltage of the high-voltage components in the electric vehicle, is the current of the high-voltage components in the electric vehicle, The power consumption of low-voltage components in electric vehicles. is the voltage of low-voltage components in electric vehicles, For low-voltage components in electric vehicles, For test time.

[0053] For example, according to the test data obtained in S104, the voltage data and current data at the same time are analyzed for energy flow, and it is set that at the second second, the voltage data is 2V and the current data is 0.2A, and the formula for calculating power consumption is obtained. The motor efficiency is calculated, and the electric drive efficiency and feeding efficiency are calculated using the following formula: in, is the total efficiency of the vehicle motor drive, is the front axle drive efficiency of the motor, is the rear axle drive efficiency of the motor, is the total efficiency of the vehicle motor feeding, is the motor front shaft feeding efficiency, is the motor rear shaft feeding efficiency, is the total wheel torque, is the total torque on the front axle, is the total torque on the rear axle, is the motor speed, is the motor bus voltage, is the total output current of the motor, is the output current of the front motor, Output current for the rear motor.

[0054] The battery internal resistance analysis is calculated based on the heat generated by the battery itself. Since the driving process is divided into driving and braking, the battery discharges during driving and charges during braking. Since the charging internal resistance and discharging internal resistance of the battery are different, the data is first divided into battery charging data and battery discharging data. Then, since the battery internal resistance is highly correlated with the battery temperature, the test data is classified and processed according to the battery temperature, with a certain temperature interval as the segmentation threshold, such as every interval Separate the data, and then fit it according to the following formula based on the current and voltage distribution of the battery. The slope of the fitting curve is the internal resistance of the battery. The internal resistance fitted by the charging data is the charging internal resistance, and the internal resistance fitted by the discharging data is the discharging internal resistance.

[0055] in, is the battery output voltage, is the battery output current, and are the coefficients to be fitted, is the fitted battery internal resistance, is the fitted open circuit voltage.

[0056] Based on the fitted battery internal resistance, a table of battery internal resistance that changes with temperature can be obtained, and then linear difference is performed to finally obtain a battery charging internal resistance map and battery discharging internal resistance map over the full temperature range.

[0057] According to the formula , the power consumption of the battery's internal resistance can be calculated. is the power consumption of the battery's internal resistance, is the battery output current, is the fitted battery internal resistance.

[0058] According to the battery water inlet temperature, water outlet temperature, and battery thermal management circuit flow, the battery heating capacity and battery cooling capacity are calculated using the following formula: in, The heating and cooling capacity outside the battery, is the specific heat capacity of the coolant, is the battery thermal management circuit flow, is the outlet temperature at the kth second, is the water inlet temperature at the kth second, For test time.

[0059] The external heating and cooling efficiency of the battery can be calculated based on the external heating amount of the battery and the external cooling amount of the battery, the external heating amount of the battery or the external heat dissipation of the battery.

[0060] in, For the heating and cooling efficiency of the battery, It is the heating power of the external heat source or the cooling power of the external heat source, wherein the heating power of the external heat source is the power consumption of the PTC, and the cooling power of the external heat source is the power consumption of the compressor.

[0061] For example, the summary vehicle energy flow indicators are shown in Table 3 below: Table 3: The energy flow data obtained according to the above method and the vehicle energy consumption data are correlated, wherein the energy flow data are multiple groups of sample index data, and the vehicle energy consumption data are multiple groups of sample energy consumption data.

[0062] Determine the correlation between the sample indicator data and the sample energy consumption data according to the following formula: in, is the correlation between the i-th sample index data and the i-th sample energy consumption data, is the set of the i-th indicator data, is the set of energy consumption data of the i-th vehicle, for The j-th sample indicator variable in for The j-th sample energy consumption variable in for 、 The joint probability density of for The marginal probability density of for The marginal probability density of , and The product of is equal to or The number of variables in a is the horizontal axis coordinate variable of the grid G, b is the vertical axis coordinate variable of the grid G, and are all positive integers, , q is or The number of variables in , j is a positive integer, j is less than or equal to q.

[0063] The sample indicator data with correlation lower than the correlation threshold are removed from the multiple groups of sample indicator data to obtain remaining sample indicator data and remaining sample energy consumption data.

[0064] Exemplarily, the correlation threshold is set to 0.7, the correlation between the first sample indicator data and the first sample energy consumption data is 0.8, and the correlation between the second sample indicator data and the second sample energy consumption data is 0.6. Depending on the size of the correlation threshold, the first sample indicator data and the first sample energy consumption data can be retained, and the second sample indicator data and the second sample energy consumption data can be removed.

[0065] The remaining sample index data and remaining sample energy consumption data are used to train the vehicle energy consumption prediction model. Figure 5 As shown in the figure, this figure is a schematic diagram of a vehicle energy consumption prediction model provided by an embodiment of the present application. In the figure, the vehicle energy consumption prediction model is divided into 7 layers. The first layer is the input layer, and the input quantity is Key energy flow indicators, the number of nodes is The second layer represents the fuzzy subspace, which is divided into 7 fuzzy subsets, namely positive large, positive medium, positive small, zero, negative small, negative medium, and negative large. Each node represents the membership function of the fuzzy set. (in, r is an integer, and , )The membership function adopts a bell-shaped function, and the formula is as follows: in, is the center of membership, is the width of the membership, and the number of nodes in this layer is , the third layer is the reasoning layer, each node output corresponds to the applicability of each rule, the number of nodes in this layer is The fourth layer is normalized calculation, and the number of nodes is The fifth layer is the output layer, and the number of nodes is 1.

[0066] Set the number of training times to 100. After completing the training, a vehicle energy consumption prediction model can be obtained.

[0067] S106: Present the analysis results to the user.

[0068] The analysis results may include the above-mentioned electric drive efficiency, power consumption of high-voltage components and low-voltage components, and power consumption of the battery's own internal resistance, etc. The processing equipment displays the energy consumption value of each component based on the test results through the monitoring interface, and can intuitively see whether the energy consumption of each component meets the requirements or exceeds the standard.

[0069] Based on the above description, the embodiment of the present application provides a vehicle energy flow analysis method based on a technical bench, in which the processing device obtains test conditions, the test conditions include a test mode and a simulated opening of the accelerator pedal, and according to the test mode and the simulated opening, the target voltage input to the vehicle control unit VCU is determined, and the target voltage is converted into an analog voltage through a digital-to-analog conversion module, and output to the VCU, so that the VCU controls the motor according to the analog voltage, and in the process of VCU controlling the motor according to the analog voltage, the vehicle energy data is collected, and the vehicle energy flow is analyzed according to the vehicle energy data. At present, when testing the electric drive efficiency under different conditions on the technical bench, the opening of the accelerator pedal can be controlled by the driver's feet. Since the vehicle will shake during the test, the stability of the manual control of the accelerator pedal is poor. Therefore, in this case, the data obtained by the test will have a large error, which will lead to poor accuracy in the vehicle energy flow analysis. It can be seen that the scheme of the present application can improve the accuracy of the vehicle energy flow analysis.

[0070] Exemplarily, the present application also proposes a portable, low-cost, vehicle-mounted high-precision data management system, such as Figure 6 As shown, this figure is a flow chart of a vehicle data management system provided in an embodiment of the present application, which can improve the accuracy of vehicle energy flow analysis.

[0071] S601. Arrangement of vehicle test data and test indicators.

[0072] The data management system includes temperature measurement module, analog acquisition module, high voltage acquisition module, CAN acquisition module, and data recording module, which supports the acquisition and recording of temperature, current, voltage, flow, CAN, CANFD and other signals. The vehicle test data and test indicators are sorted according to the test matrix below.

[0073] The range test 221, charging performance test 222, resistance decomposition test 223 and electric drive efficiency test 224 under different temperature conditions. The range test 221 includes vehicle testing at high temperature, low temperature, ultra-low temperature, normal temperature and other temperature points. The charging performance test 222 includes normal temperature, high temperature, low temperature, ultra-low temperature and other temperature point tests. The resistance decomposition test 223 includes the mechanical resistance of the transmission system, caliper resistance, bearing resistance and other resistances at different temperatures and different vehicle speeds. The electric drive efficiency test 224 mainly includes the electric drive efficiency at different temperatures, such as normal temperature and low temperature conditions. During the test, the sensor data and CAN bus data are collected synchronously.

[0074] S602, uploading the sorted data to the data management system.

[0075] The data management system can input vehicle energy flow data and indicators with one click, and has the functions of automatically analyzing performance indicators and process data between different vehicles, analyzing the development trend of vehicle indicators, and generating analysis reports with one click.

[0076] Specifically, the test data is classified according to test items, test conditions, test conditions, and test methods, and the classified data is stored separately in two categories: test indicators and test process data. Standard indicator names and parameter names are used to record various implementation indicators and process data. Then all the data of a car model is compressed and packaged and uploaded to the data management system. The system can automatically identify the data according to the data classification, and then display the vehicle performance indicators and process data on the interface. At the same time, it supports switching the test data on the interface according to test items, test conditions, test conditions, and test methods.

[0077] S603, vehicle performance display.

[0078] You can select a certain vehicle model, determine the test items, test conditions, test conditions, and test methods. The system can intuitively display the vehicle energy consumption, the energy consumption and proportion of each component, and the test process data.

[0079] S604, comparison of multiple models.

[0080] You can select multiple vehicles in the data management system to compare the size of different indicators and the size of test process data under the same test items, test conditions, test conditions, and test methods. By comparing multiple vehicle indicators, you can intuitively see the gap between indicators of different models, and thus find out the performance indicators that need to be optimized.

[0081] S605. Intelligent analysis.

[0082] At the same time, you can perform intelligent analysis on a single test indicator, select the vehicle model that needs intelligent analysis, then select the test item, determine the test indicator to be analyzed, screen the test conditions, test methods, and test conditions, and use the maximum, minimum, average, median, standard deviation, kurtosis, and skewness of the indicator data of all vehicle models to reflect the degree of dispersion and distribution trend of vehicle test indicators. The indicator data is displayed in the form of scatter plots, bar charts, and normal distribution charts. In addition, it also supports trend analysis of vehicle indicators according to vehicle parameters such as vehicle wheelbase, vehicle year, and vehicle price. Through intelligent analysis, you can see the ranking of the test indicators of a certain model among many models, so as to determine whether the indicator needs to be optimized.

[0083] Combination of the above Figures 1 to 6 The vehicle energy flow analysis method based on the technical bench provided in the embodiment of the present application is introduced in detail. The device and equipment provided in the embodiment of the present application will be introduced in conjunction with the accompanying drawings.

[0084] like Figure 7 As shown, this figure is a schematic diagram of a vehicle energy flow analysis device based on a technical bench provided in an embodiment of the present application, and the device includes: An acquisition module 701 is used to acquire test conditions, wherein the test conditions include a test mode and a simulated opening of an accelerator pedal; The determination module 702 is used to determine the target voltage input to the vehicle control unit VCU according to the test mode and the simulated opening; convert the target voltage into an analog voltage through the digital-to-analog conversion module, and output it to the VCU, so that the VCU controls the motor according to the analog voltage; The acquisition module 703 is used to collect vehicle energy data when the VCU controls the motor operation according to the analog voltage; The analysis module 704 is used to analyze the vehicle energy flow according to the vehicle energy data.

[0085] Optionally, the obtaining of the test conditions includes: Presenting a test interface to a user, the test interface comprising a first configuration area for a test mode and a second configuration area for a simulated opening of an accelerator pedal; The test mode configured by the user in the first configuration area and the simulated opening of the accelerator pedal configured in the second configuration area are obtained.

[0086] Optionally, the accelerator pedal includes a first positive output terminal, a first negative output terminal, a second positive output terminal, and a second negative output terminal, the VCU includes a first positive input terminal, a first negative input terminal, a second positive input terminal, and a second negative input terminal, and the digital-to-analog conversion module includes a third positive output terminal and a fourth positive output terminal; The first positive output terminal is disconnected from the first positive input terminal, the second positive output terminal is disconnected from the second positive input terminal, the third positive output terminal is connected to the first positive input terminal, the fourth positive output terminal is connected to the second positive input terminal, the first negative output terminal is connected to the first negative input terminal, and the second negative output terminal is connected to the second negative input terminal.

[0087] Optionally, after collecting the vehicle energy data, the method further includes: Generating multiple groups of sample index data and multiple groups of sample energy consumption data according to the vehicle energy data; Determine the correlation between the sample indicator data and the sample energy consumption data; The sample indicator data with correlation lower than the correlation threshold are removed from the multiple groups of sample indicator data to obtain remaining sample indicator data and remaining sample energy consumption data; The remaining sample index data and the remaining sample energy consumption data are used to train a vehicle energy consumption prediction model.

[0088] Optionally, determining the correlation between the sample indicator data and the sample energy consumption data includes: in, is the correlation between the i-th sample index data and the i-th sample energy consumption data, is the set of the i-th indicator data, is the set of energy consumption data of the i-th vehicle, for The j-th sample indicator variable in for The j-th sample energy consumption variable in for 、 The joint probability density of for The marginal probability density of for The marginal probability density of , and The product of is equal to or The number of variables in a is the horizontal axis coordinate variable of the grid G, b is the vertical axis coordinate variable of the grid G, and are all positive integers, , q is or The number of variables in , j is a positive integer, j is less than or equal to q.

[0089] Optionally, the method further includes: Obtain the indicator data to be predicted; The index data to be predicted is input into the vehicle energy consumption prediction model to obtain the vehicle energy consumption corresponding to the index data to be predicted.

[0090] Optionally, the method further includes: Present the analysis results to the user.

[0091] The vehicle energy flow analysis device based on the technical bench according to the embodiment of the present application may correspond to the method described in the embodiment of the present application, and the above-mentioned other operations and / or functions of each module / unit of the vehicle energy flow analysis device based on the technical bench are respectively to realize Figure 1 For the sake of brevity, the corresponding processes of each method in the illustrated embodiment are not described in detail here.

[0092] The present application also provides a computing device. Figure 8 As shown, this figure is a schematic diagram of a computing device provided by an embodiment of the present application, and the computing device 800 includes a bus 801, a processor 802, a communication interface 803 and a memory 804. The processor 802, the memory 804 and the communication interface 803 communicate through the bus 801.

[0093] The bus 801 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0094] The processor 802 may be any one or more of a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0095] The communication interface 803 is used for communicating with the outside.

[0096] The memory 804 may include a volatile memory, such as a random access memory (RAM). The memory 804 may also include a non-volatile memory, such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD), or a solid state drive (SSD).

[0097] The memory 804 stores executable codes, and the processor 802 executes the executable codes to perform a vehicle energy flow analysis method based on a technology bench.

[0098] Specifically, in implementing Figure 7 In the case of the embodiment shown, and Figure 7 When each module or unit of the vehicle energy flow analysis device based on the technical bench described in the embodiment is implemented by software, the execution Figure 7 The software or program code required for the functions of each module / unit in the system may be partially or completely stored in the memory 804. The processor 802 executes the program code corresponding to each unit stored in the memory 804 to execute the vehicle energy flow analysis method based on the technical bench.

[0099] The embodiment of the present application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that can be stored by a computing device or a data storage device such as a data center containing one or more available media. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, a tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid-state hard disk). The computer-readable storage medium includes instructions that instruct the computing device to execute the above-mentioned vehicle energy flow analysis method based on the technical bench.

[0100] The embodiment of the present application further provides a computer program product, which includes one or more computer instructions. When the computer instructions are loaded and executed on a computing device, the process or function described in the embodiment of the present application is generated in whole or in part.

[0101] The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer or data center to another website, computer or data center via wired (e.g., coaxial cable, optical fiber) or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0102] When the computer program product is executed by a computer, the computer executes any method of the vehicle energy flow analysis method based on a technical bench. The computer program product may be a software installation package, and when any method of the vehicle energy flow analysis method based on a technical bench needs to be used, the computer program product may be downloaded and executed on a computer.

[0103] The descriptions of the processes or structures corresponding to the above-mentioned figures have different emphases. For parts that are not described in detail in a certain process or structure, please refer to the relevant descriptions of other processes or structures.

[0104] The above description is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application should be included in the protection scope of the present application.

Claims

1. A vehicle energy flow analysis method based on a technical bench, It is characterized in that The method comprises: Acquiring test conditions, wherein the test conditions include a test mode and a simulated opening of an accelerator pedal; Determining a target voltage input to a vehicle control unit VCU according to the test mode and the simulated opening; The target voltage is converted into an analog voltage by a digital-to-analog conversion module, and outputted to the VCU, so that the VCU controls the motor according to the analog voltage; collecting vehicle energy data during the process in which the VCU controls the operation of the motor according to the simulated voltage; The vehicle energy flow is analyzed based on the vehicle energy data.

2. The method according to claim 1, It is characterized in that The obtaining of test conditions comprises: Presenting a test interface to a user, the test interface comprising a first configuration area for a test mode and a second configuration area for a simulated opening of an accelerator pedal; The test mode configured by the user in the first configuration area and the simulated opening of the accelerator pedal configured in the second configuration area are obtained.

3. The method according to claim 1, It is characterized in that The accelerator pedal includes a first positive output terminal, a first negative output terminal, a second positive output terminal, and a second negative output terminal, the VCU includes a first positive input terminal, a first negative input terminal, a second positive input terminal, and a second negative input terminal, and the digital-to-analog conversion module includes a third positive output terminal and a fourth positive output terminal; The first positive output terminal is disconnected from the first positive input terminal, the second positive output terminal is disconnected from the second positive input terminal, the third positive output terminal is connected to the first positive input terminal, the fourth positive output terminal is connected to the second positive input terminal, the first negative output terminal is connected to the first negative input terminal, and the second negative output terminal is connected to the second negative input terminal.

4. The method according to any one of claims 1 to 3, It is characterized in that After collecting the vehicle energy data, the method further includes: Generating multiple groups of sample index data and multiple groups of sample energy consumption data according to the vehicle energy data; Determine the correlation between the sample indicator data and the sample energy consumption data; The sample indicator data with correlation lower than the correlation threshold are removed from the multiple groups of sample indicator data to obtain remaining sample indicator data and remaining sample energy consumption data; The remaining sample index data and the remaining sample energy consumption data are used to train a vehicle energy consumption prediction model.

5. The method according to claim 4, It is characterized in that Determining the correlation between the sample indicator data and the sample energy consumption data includes: in, is the correlation between the i-th sample index data and the i-th sample energy consumption data, is the set of the i-th indicator data, is the set of energy consumption data of the i-th vehicle, for The j-th sample indicator variable in for The j-th sample energy consumption variable in for 、 The joint probability density of for The marginal probability density of for The marginal probability density of , and The product of is equal to or The number of variables in a is the horizontal axis coordinate variable of the grid G, b is the vertical axis coordinate variable of the grid G, and are all positive integers, , q is or The number of variables in , j is a positive integer, j is less than or equal to q.

6. The method according to claim 5, It is characterized in that The method further comprises: Obtain the indicator data to be predicted; The index data to be predicted is input into the vehicle energy consumption prediction model to obtain the vehicle energy consumption corresponding to the index data to be predicted.

7. The method according to claim 1, It is characterized in that The method further comprises: Present the analysis results to the user.

8. A vehicle energy flow analysis device based on a technical bench, It is characterized in that The device comprises: An acquisition module, used for acquiring test conditions, wherein the test conditions include a test mode and a simulated opening of an accelerator pedal; a determination module, configured to determine a target voltage to be input to a vehicle control unit VCU according to the test mode and the simulated opening; convert the target voltage into an analog voltage through a digital-to-analog conversion module, and output the analog voltage to the VCU, so that the VCU controls the motor according to the analog voltage; A collection module, used for collecting vehicle energy data when the VCU controls the motor operation according to the analog voltage; An analysis module is used to analyze the vehicle energy flow according to the vehicle energy data.

9. A computing device, It is characterized in that including memory and processor; One or more computer programs are stored in the memory, and the one or more computer programs include instructions; when the instructions are executed by the processor, the computing device executes the method as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium, It is characterized in that The computer-readable storage medium is used to store a computer program, and the computer program is used to execute the method according to any one of claims 1 to 7.

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