In view of the development status of the domestic automobile industry, this paper proposes a high-speed, low-cost, high-efficiency vehicle electronic control system rapid development method, and establishes a corresponding rapid development system. The development system can maximize the simulation of the actual vehicle operating conditions under various operating conditions, and realize the rapid development of the ABS control system under laboratory conditions. The entire development process includes control system conceptual design, system modeling, system offline simulation, automatic code generation, hardware-in-the-loop real-time simulation and final product testing. Because the development platform is unified, the various development stages are closely connected to achieve interactive parallel communication, which greatly overcomes the redundant intermediate links and saves time and cost. Real-time simulation requires an ABS dynamic system model that reflects the essence of the problem. It is the most important component of the vehicle ABS 'speed determination development system, which is directly related to the development efficiency and accuracy of the controller. ABS dynamic system model mainly includes vehicle model, tire neural network model, hydraulic system model and brake model. The in-depth study of the tire neural network model has contributed to the real vehicle test program for obtaining the tire neural network model learning samples, and conducted corresponding experiments. In order to verify the correctness and accuracy of the ABS dynamic model from the three aspects of longitudinal, transverse and dynamic characteristics of the combined working conditions, road tests under three working conditions were carried out using test sample vehicles, namely vehicle linear braking test, Pure steering test and brake steering test. All test results show that the ABS dynamic system model established in this paper is theoretically correct, and basically meets the requirements of simulation accuracy and subsequent research work.
In view of the development status of the domestic automobile industry, this paper proposes a high-speed, low-cost, high-efficiency vehicle electronic control system rapid development method, and establishes a corresponding rapid development system. The development system can maximize the simulation of the actual vehicle operating conditions under various operating conditions, and realize the rapid development of the ABS control system under laboratory conditions. The entire development process includes control system conceptual design, system modeling, system offline simulation, automatic code generation, hardware-in-the-loop real-time simulation and final product testing. Because the development platform is unified, the various development stages are closely connected to achieve interactive parallel communication, which greatly overcomes the redundant intermediate links and saves time and cost.<br> Real-time simulation requires an ABS dynamic system model that reflects the essence of the problem. It is the most important component of the vehicle ABS 'speed determination development system, which is directly related to the development efficiency and accuracy of the controller. ABS dynamic system model mainly includes vehicle model, tire neural network model, hydraulic system model and brake model. The in-depth study of the tire neural network model has contributed to the real vehicle test program for obtaining the tire neural network model learning samples, and conducted corresponding experiments. In order to verify the correctness and accuracy of the ABS dynamic model from the three aspects of longitudinal, transverse and dynamic characteristics of the combined working conditions, road tests under three working conditions were carried out using test sample vehicles, namely vehicle linear braking test, Pure steering test and brake steering test. All test results show that the ABS dynamic system model established in this paper is theoretically correct, and basically meets the requirements of simulation accuracy and subsequent research work.
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