The Design And Control Strategy Of Electromechanical Coupling Braking System For Formula E-racing Car

With the development of society and economy,the problems of environmental pollution and energy shortage have become increasingly prominent.Energy conservation and environmental protection have become one of the themes in the development of automobile technology.Countries around the world have successively issued timetables for the ban on the sale of fuel vehicles,and new energy vehicles have become an inevitable trend in the development of the automobile industry in China and even the world.In order to tap and cultivate future electric vehicle engineering talents,the Society of Automotive Engineers of China established the Formula Student Electric China(FSEC)in 2015.Regenerative braking technology can reduce energy consumption and improve energy utilization in endurance tests.In order to improve the performance of endurance races,this paper takes the Changsha University of Science and Technology electric formula car as the research object,and designs an electromechanical coupling braking system suitable for electric formula cars.Based on this,a regenerative braking control strategy based on fuzzy neural network is proposed,and the cosimulation analysis is carried out.The details are as follows:1)According to the actual vehicle verification parameters,the vehicle dynamics model is established in Carsim;the working principle of the drive motor and power battery is emphatically analyzed for the structure of the regenerative braking system,which provides data support for building the simulink model:combined with the calibration data of the motor bench,the power limit calculation of the drive motor is carried out;the performance of the single battery is experimentally tested,the model is established by using the Keithley DC power supply equipment,and the charging and discharging efficiency of the power battery is obtained.2)According to the characteristics of regenerative braking and hydraulic braking,a layered control strategy of electromechanical coupling braking is designed;aiming at the problems existing in the current power-assisted braking control mechanism,a link-type power-assisted brake assembly is designed,and the The double closed-loop PI control strategy is used to control the corresponding action of the booster motor,and the booster system is realized according to the braking demand,and the tracking target of the desired braking pressure is achieved.3)Using the method of "basic torque+acceleration compensation",a driving torque control system is established;from the perspective of front and rear axle braking force distribution and regenerative braking ratio,the optimization goal is to maximize energy recovery,and ideal According to the braking conditions and the requirements of ECE R13 regulations,the braking force distribution coefficient of the front and rear axles is determined;considering the influence of parameters such as braking intensity,vehicle speed and battery SOC,a fuzzy controller for regenerative braking distribution is established.According to the inherent properties of the membership function,BP is adopted The neural network algorithm is used to optimize it,and the fuzzy neural network controller is obtained,which realizes the optimization of regenerative braking force distribution.4)The Carsim/Simulink co-simulation platform is built to verify the effectiveness of the electromechanical coupling regenerative braking control strategy under the endurance condition of the formula competition and the typical braking condition.The results show that the new control strategy can improve the energy recovery rate by 9.1%compared with the existing control strategy under the durable working condition.Under typical braking conditions,the effects of different initial vehicle speeds,braking intensity and battery SOC on braking energy recovery are analyzed.In this paper,some achievements have been made in the research of on-line braking and regenerative braking.Based on the electric power-assisted braking system to coordinate the regenerative braking of the motor,through the regenerative braking control strategy based on fuzzy neural network,high energy recovery rate is achieved while ensuring the braking safety.