The Design And Research On The Key Technology Of

With the increasingly serious environmental problems and energy crisis, thedevelopment of electric vehicles gets more and more attention. Because electric vehiclesenergy feedback control technology can extend its mileage through reclaim and reuse thekinetic energy for braking, the technology became the research focus in the field of electricvehicles. But now the electric car energy feedback technology is not still mature, mainly inthe low regenerative efficiency, the complex and expensive systems and other aspects. Atthe same time, the regenerative efficiency depends on the motor controllers and energyfeedback control algorithm. So, in this thesis improve regenerative efficiency of electricvehicles as the goal, the brushless DC motor for electric vehicle as the research object. Theelectric vehicle energy feedback control algorithm and controller are researched.Meanwhile, energy feedback test platform is designed.After analyzing the structure and working principle of brushless DC motor, athree-phase full-controlled drive circuit and PWM-ON-modulated electric operation controlstrategy is adopted, and the double-loop speed control system is designed. On this basis, theanalysis of the brushless DC motor energy feedback control theory and control strategies.And then the energy feedback control system for electric vehicle is designed based onadaptive fuzzy neural network, and the fuzzy neural network is trained through BP trainingalgorithm. The training results show that the control system has fast rate of convergenceand high approximation accuracy.Then in the MATLAB/Simulink environment, energy feedback control system offuzzy neural network for brushless DC motor is established, and the system is comparedwith the energy feedback control system not applied fuzzy neural network. Simulationresults show that the energy feedback control system designed in this thesis can effectivelyimprove the regenerative efficiency of electric vehicles, thereby extending the mileage ofelectric vehicles; while the motor speed change is more stable and braking effect is good.Finally, the electric operation of system and the energy feedback control system isintegrated rationally and effectively. Based on the same hardware configuration, electricoperation and energy feedback control are achieved through relevant software, thecontroller after integration reduces the complexity and cost of electric vehicle controlsystem structure.After being verified to satisfy the requirement of the road test, the controller isinstalled in an electric vehicle, and compared the performance of energy feedback control with the original controller of the electric vehicle. The test results show that compared withthe original controller, fuzzy neural network and the controller has the high energyefficiency, which designed for energy feedback control. Furthermore, the more the frequentbraking, the higher the regenerative efficiency. Besides, this article also designed theelectric vehicle energy feedback test platform that can fully evaluate energy feedbackcontrol system performance.