Control method and control device of electric vehicle controller and electric vehicle

Abstract

The application relates to the technical field of electric vehicle control, in particular to a control method and a control device of an electric vehicle controller and an electric vehicle, the method comprising the following steps: collecting dynamic parameters of an inductive controller and influence factors influencing steering performance when the electric vehicle is running; preprocessing the dynamic parameters and the influence factors, constructing a new data set, and importing the constructed processing model to perform parameter analysis; setting key characteristic parameters and constraint conditions in the processing model, and analyzing the steering performance influence factors of the key characteristics; using a fuzzy control strategy to solve the steering performance influence factors, and importing the output result into the inductive controller to perform steering control. The application effectively solves the wheel deflection problem of the electric vehicle when turning, improves the experience of users, reduces the vibration feeling, and maintains stable steering work.

Description

Technical Field

[0001] This invention relates to the field of electric vehicle control technology, and in particular to a control method, control device, and electric vehicle for an electric vehicle controller. Background Technology

[0002] Electric vehicles are vehicles that use onboard power sources to drive their wheels with electric motors and meet all road traffic and safety regulations. Based on the type of power source, electric vehicles can be simply divided into three types: pure electric vehicles, hybrid electric vehicles, and fuel cell vehicles.

[0003] Current electric vehicles use stored electrical energy from batteries as their power source. The most prominent problem in practical applications is their short driving range. One effective way to increase the driving range of electric vehicles is to reduce the vehicle's weight. After reducing the vehicle's weight, the shock absorption strength must be weakened to ensure driving comfort. When the vehicle turns, the wheels deflect under the driver's forced twisting. The friction between the wheels and the ground forces the vehicle to turn, and the vehicle generates a force to maintain its original direction due to inertia.

[0004] On one hand, the torque generated by this force relative to the fulcrum of friction is converted into a large offset weight pressing outwards. This offset weight is transmitted to the outer shock absorber, causing the weakened shock absorber to compress significantly, resulting in the vehicle tilting outwards. On the other hand, this force also generates a lateral thrust that moves the vehicle in its original direction. Due to the friction between the tires and the ground forcing the vehicle to steer, the inner shock absorber is pushed upwards by the shift of the vehicle's center of gravity outwards, further increasing the degree of vehicle tilt and potentially causing the vehicle to roll over, resulting in an accident. Therefore, to a certain extent, the weakened shock absorber increases the probability of the vehicle rolling over.

[0005] When electric vehicles are turning and driving, they are subject to various limitations such as road surface and drive shaft, which can lead to vibration problems of the whole vehicle or parts of the vehicle body, instability of the vehicle body or rollover problems. If the vibration frequency exceeds a certain standard, it will seriously affect the driver's driving comfort. If the vehicle body is unstable or the turning speed is too fast and a rollover occurs, it will endanger the driver's life and property safety.

[0006] How to effectively solve the wheel deflection problem that occurs when electric vehicles turn, improve the user experience, and maintain stable steering while reducing vibration is a problem that needs to be addressed. In summary, electric vehicles currently face the following issues: 1) Electric vehicles are prone to wheel deflection when turning, which can lead to rollover; 2) Using shock absorbers to reduce vibration and improve comfort can easily cause vehicle instability; 3) It cannot effectively control the steering of electric vehicles traveling at high speeds. Summary of the Invention

[0007] This invention provides a control method, control device, and electric vehicle controller for electric vehicles, ensuring smooth and comfortable driving and reducing steering instability caused by influencing factors.

[0008] To achieve the objective of this invention, the technical solution adopted is: a control method for an electric vehicle controller, the method comprising: Collect dynamic parameters of the sensor controller and factors affecting steering performance when the electric vehicle is in motion; Preprocess dynamic parameters and influencing factors, construct a new dataset, and import it into the constructed processing model for parameter analysis; Key feature parameters and constraints are set within the processing model, and the influencing factors of steering performance of key features are analyzed. The steering performance influencing factors are solved using a fuzzy control strategy, and the output is imported into the inductive controller for steering control.

[0009] As an optimized solution of the present invention, the collection specifically includes: A model of an electric vehicle is constructed in 3D software and then imported into a simulation platform for simulated driving. Add dynamic parameters to the sensor controller, input them into the simulation platform, and observe the operating status; The simulation platform has finished running and outputs the dynamic parameters of the sensor controller during operation. To identify the factors influencing the steering performance of an electric vehicle's sensor controller during driving.

[0010] As an optimized solution of the present invention, the dynamic parameters of the sensing controller include: motor speed, driving force of the drive shaft, size of the transmission and differential, speed frequency of the sensing controller, traction force between the drive wheel and the road surface, reaction force between the vehicle mass and the ground, and steering stability force of the vehicle.

[0011] As an optimization of the present invention, the factors affecting steering performance include one or more of the following: weather factors, road condition factors, sensor controller factors, vehicle vibration factors, electric vehicle service life factors, electric vehicle architecture material factors, impact and wear factors, and environmental corrosion factors.

[0012] As an optimized solution of the present invention, the preprocessing dynamic parameters and influencing factors include: Cleaning the collected data: Validating the data, removing duplicate data, and deleting missing values; The collected data after cleaning is standardized and divided into a dynamic parameter set and an influencing factor set, where x = (X-min) / (max-min). Where x is the standardized data, X is the cleaned data, min is the minimum value of X, and max is the maximum value of X; Define the set of dynamic parameters and the set of influencing factors as a new dataset.

[0013] As an optimized solution of the present invention, the key characteristic parameters include the rotational frequency of the sensing controller, the traction force between the drive wheel and the road surface, the reaction force between the vehicle mass and the ground, and the vehicle steering stability force.

[0014] As an optimized solution of the present invention, the steering stiffness, steering torsional stiffness and wheel load deformation of the electric vehicle are used as constraints.

[0015] To achieve the objective of this invention, the technical solution adopted is: a control device for a control method of an electric vehicle controller, comprising: The data acquisition module collects dynamic parameters of the sensor controller and factors affecting steering performance when the electric vehicle is in motion. The data processing center includes computing units, detection units, and a database. Calculation unit: used to process the maximum steering limit and minimum wheel adhesion coefficient of electric vehicles during operation; The detection unit is used to compare the maximum steering limit value and the minimum wheel adhesion coefficient obtained by the calculation unit with the corresponding values ​​and corresponding parameter tolerance ranges in the electric vehicle steering standard, and to analyze the steering performance influencing factors based on the comparison results. Database: Used to identify the data information within the acquisition module and to classify and store it.

[0016] As an optimized solution of the present invention, the control device further includes an input / output management module and a control module. The input / output management module is connected to the computing unit, and the control module is used to receive the calculation results transmitted by the input / output management module, perform command execution judgment on the calculation results, and control the steering of the wheels.

[0017] To achieve the objective of this invention, the technical solution adopted is: an electric vehicle, the electric vehicle including the control device of the electric vehicle controller.

[0018] The present invention has positive effects: 1) The stability of the method of the present invention is far higher than that of the traditional method. The method of the present invention is to control the vehicle steering by precisely adjusting the dynamic steering driving parameters of the induction controller. It redefines the parameters that may affect the dynamic performance, ensures the smoothness and comfort of electric vehicle driving, reduces steering instability caused by influencing factors, and avoids wheel deflection. 2) This invention effectively solves the problem of wheel deflection when electric vehicles turn, improves the user experience, and maintains stable steering while reducing vibration. Attached Figure Description

[0019] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0020] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a flowchart of a fuzzy control strategy. Detailed Implementation

[0021] like Figure 1 As shown, this invention discloses a control method for an electric vehicle controller, the method comprising: Collect dynamic parameters of the sensor controller and factors affecting steering performance when the electric vehicle is in motion; The dynamic parameters and influencing factors are preprocessed to construct a new dataset, which is then imported into the processing model for parameter analysis. The parameter analysis process of the processing model includes setting key feature parameters and constraints, processing relevant parameters, and comparison and judgment.

[0022] Within the processing model, the rotational frequency of the sensor controller, the traction force between the drive wheels and the road surface, the reaction force between the vehicle mass and the ground, and the vehicle's steering stability force are set as key characteristic parameters. The steering stiffness, steering torsional stiffness, and wheel deformation under load of the electric vehicle are used as constraints. Based on these key characteristic parameters and constraints, the maximum steering limit and minimum wheel adhesion coefficient of the electric vehicle are processed. The maximum steering limit and minimum wheel adhesion coefficient are compared with their corresponding values ​​and tolerance ranges in the electric vehicle steering standard. Based on the comparison results, a steering performance influence factor is generated to characterize whether the relevant steering parameters are within the allowable range. When the comparison results indicate that the relevant steering parameters exceed the corresponding steering standard values ​​or parameter tolerance ranges, a warning is issued in the generated analysis results. The steering performance influence factor referred to in this application is the comparison result of the aforementioned maximum steering limit and minimum wheel adhesion coefficient relative to their corresponding steering standard values ​​and parameter tolerance ranges.

[0023] A fuzzy control strategy is used to solve for the factors affecting steering performance, and the output is then fed into an inductive controller for steering control. For example... Figure 2 As shown, the steering performance influencing factors are input into the fuzzy control flow and compared with the sensor feedback signals. The comparison result is fuzzified after A / D conversion and control variable calculation. The fuzzified signal serves as the input to the fuzzy control rules to complete fuzzy inference. The inference result is defuzzified and converted to D / A before being output to the actuator. The fuzzy control rules are developed based on the experience of operators or experts. Sensors detect the vehicle state and return feedback signals to the comparison stage to form closed-loop control.

[0024] The data collection specifically includes: A model of an electric vehicle is constructed in 3D software and then imported into a simulation platform for simulated driving. Add dynamic parameters to the induction controller and input them into the simulation platform to observe the operating status of the electric vehicle; the simulation platform is the MATLAB simulation platform, and the electric vehicle model is a car model drawn in 3D software.

[0025] The simulation platform has finished running and outputs the dynamic parameters of the sensor controller during operation. This involves identifying factors affecting the steering performance of an electric vehicle's sensor controllers during operation. Specifically, it utilizes serial port protocol technology to retrieve all factors within a network database that might influence steering performance during vehicle operation.

[0026] The dynamic parameters of the sensor controller include: motor speed, drive force of the drive shaft, size of the transmission and differential, speed frequency of the sensor controller, traction force between the drive wheels and the road surface, reaction force between the vehicle mass and the ground, and steering stability force of the vehicle. These dynamic parameters are obtained using intelligent detection tools.

[0027] Factors affecting steering performance include one or more of the following: weather conditions, road conditions, sensor controller characteristics, vehicle vibration, electric vehicle age, electric vehicle architecture materials, impact and wear, and environmental corrosion. Weather conditions include rain, snow, frost, and heavy rain; road conditions include uneven surfaces, mud, and mountain roads; and sensor controller characteristics include inaccurate parameters, command execution delays, poor real-time performance, and excessively high engine speeds. Preprocessing dynamic parameters and influencing factors include: Cleaning the collected data: Validating the data, removing duplicate data, and deleting missing values; The collected data after cleaning is standardized and divided into a dynamic parameter set and an influencing factor set, where x = (X-min) / (max-min). Where x is the standardized data, X is the cleaned data, min is the minimum value of X, and max is the maximum value of X; Define the set of dynamic parameters and the set of influencing factors as a new dataset.

[0028] Key characteristic parameters include the rotational frequency of the sensor controller, the traction force between the drive wheels and the road surface, the reaction force between the vehicle mass and the ground, and the vehicle steering stability force.

[0029] The steering stiffness, steering torsional stiffness, and wheel load deformation of the electric vehicle are used as constraints.

[0030] A control device employing a control method for an electric vehicle controller includes: The data acquisition module collects dynamic parameters of the sensor controller and factors affecting steering performance when the electric vehicle is in motion. The data processing center includes a computing unit, a detection unit, and a database. The data processing center module is connected to the acquisition module and is used to receive the acquired data and store it in the database.

[0031] Calculation unit: used to process the maximum steering limit and minimum wheel adhesion coefficient of electric vehicles during operation; The detection unit is used to compare the maximum steering limit value and the minimum wheel adhesion coefficient obtained by the calculation unit with the corresponding values ​​and corresponding parameter tolerance ranges in the electric vehicle steering standard, and to analyze the steering performance influencing factors based on the comparison results. Database: Used to identify the data information within the acquisition module and to classify and store it.

[0032] The control device also includes an input / output management module and a control module. The input / output management module is connected to the computing unit, and the control module receives the calculation results transmitted by the input / output management module, performs command execution judgment on the calculation results, and controls the wheel steering. The input / output management module, connected to the computing unit, transmits data streams and parameter information, manages the system's internal operating parameters and data, and outputs the data processed by the computing unit.

[0033] An electric vehicle, including a control device for an electric vehicle controller.

[0034] To verify and illustrate the technical effects of the method used in this invention, this embodiment selects a traditional electric vehicle control method and the method of this invention for testing and comparison. The test results are compared using scientific demonstration methods to verify the real effects of the method of this invention.

[0035] Traditional electric vehicle control methods have limited applicability, optimizing only vehicle braking without considering kinetic energy parameters and factors that may affect steering performance. This fails to improve vehicle stability during cornering. To verify that the method of this invention offers lower vehicle transmission vibration, higher comfort, and higher steering stability compared to traditional methods, this embodiment compares real-time measurements of a specific model of electric vehicle using both methods. The steering stability at different speeds is obtained, with levels 1-3 indicating stability, 4-6 indicating slight instability, and 7-10 indicating instability. The test data are shown in the table below. Table 1: Comparison of Test Results.

[0036] 40 3 1 60 3 1 100 5 2 120 7 3 Referring to Table 1, traditional electric vehicle control methods have not effectively optimized the stability of the test vehicle. At the same speed, the stability of the method of this invention is far superior to that of the traditional method. The main reason is that the method of this invention focuses on the precise control of the dynamic steering parameters of the induction controller for vehicle steering control. It redefines the parameters that may affect dynamic performance, ensuring the smoothness and comfort of the electric vehicle during driving and reducing steering instability caused by influencing factors. As shown in Table 1, this verifies the high comfort and stability of the method of this invention.

[0037] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A control method for an electric vehicle controller, characterized in that: The method includes: Collect dynamic parameters of the sensor controller and factors affecting steering performance when the electric vehicle is in motion; The dynamic parameters and influencing factors are validated, duplicate data are removed, and missing values ​​are deleted. The datasets are then standardized using the formula x = (X - min) / (max - min) and categorized into a dynamic parameter set and an influencing factor set to form a new dataset. Here, x represents the standardized data, X represents the cleaned data, min is the minimum value of X, and max is the maximum value of X. This new dataset is then imported into a processing model. The model uses the rotational frequency of the sensor controller, the traction force between the drive wheels and the road surface, the reaction force between the vehicle mass and the ground, and the vehicle's steering stability force as key characteristic parameters, and the steering stiffness, steering torsional stiffness, and wheel deformation as constraints. In the processing model, based on the key feature parameters and constraints, the maximum steering limit value and the minimum wheel adhesion coefficient during electric vehicle operation are processed. The maximum steering limit value and the minimum wheel adhesion coefficient are compared with the corresponding values ​​and corresponding parameter tolerance ranges in the electric vehicle steering standard. Based on the comparison results, a steering performance influence factor is formed to characterize whether the relevant steering parameters are within the allowable range. The steering performance influence factor is input into the fuzzy control process, compared with the sensor feedback signal, and sequentially performs A / D conversion, control variable calculation, fuzzification, fuzzy inference based on fuzzy control rules, defuzzification, and D / A conversion. The obtained control result is output to the sensor controller for steering control.

2. The control method for an electric vehicle controller according to claim 1, characterized in that: The data collection specifically includes: A model of an electric vehicle is constructed in 3D software and then imported into a simulation platform for simulated driving. Add dynamic parameters to the sensor controller, input them into the simulation platform, and observe the operating status; The simulation platform has finished running and outputs the dynamic parameters of the sensor controller during operation. To identify the factors influencing the steering performance of an electric vehicle's sensor controller during driving.

3. The control method for an electric vehicle controller according to claim 2, characterized in that: The dynamic parameters of the sensor controller include: motor speed, drive force of the drive shaft, size of the transmission and differential, speed frequency of the sensor controller, traction force between the drive wheels and the road surface, reaction force between the vehicle mass and the ground, and steering stability force of the vehicle.

4. The control method for an electric vehicle controller according to claim 2, characterized in that: Factors affecting steering performance include one or more of the following: weather factors, road conditions, sensor controller factors, vehicle vibration factors, electric vehicle service life factors, electric vehicle architecture material factors, impact and wear factors, and environmental corrosion factors.

5. A control device employing the control method of an electric vehicle controller according to any one of claims 1-4, characterized in that: include: The data acquisition module collects dynamic parameters of the sensor controller and factors affecting steering performance when the electric vehicle is in motion. The data processing center includes computing units, detection units, and a database. Calculation unit: used to process the maximum steering limit and minimum wheel adhesion coefficient of electric vehicles during operation; The detection unit is used to compare the maximum steering limit value and the minimum wheel adhesion coefficient obtained by the calculation unit with the corresponding values ​​and corresponding parameter tolerance ranges in the electric vehicle steering standard, and to analyze the steering performance influencing factors based on the comparison results. Database: Used to identify the data information within the acquisition module and to classify and store it.

6. The control device for an electric vehicle controller according to claim 5, characterized in that: The control device also includes an input / output management module and a control module. The input / output management module is connected to the computing unit, and the control module is used to receive the calculation results transmitted by the input / output management module, perform command execution judgment on the calculation results, and control the steering of the wheels.

7. An electric vehicle, characterized in that: The electric vehicle includes a control device for an electric vehicle controller as described in claim 5 or 6.

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