| With the continuous expansion of the automobile market,the number of automobile preservation is also increasing,and the energy shortage and environmental crisis are more and more serious.The rapid development of electric vehicles provides a more effective solution to these two problems.But at present,the battery technology is not fully mature,and there is no perfect charging network system,which leads to the short driving range of electric vehicles,which seriously restricts its further development.Therefore,many endurance technologies have been widely studied,among which regenerative braking technology has become an important research direction of many scholars due to its characteristics of recovering part of energy in the process of vehicle braking.However,motor regenerative braking can not meet all the braking requirements,so it is necessary to form a composite braking system with mechanical braking system.Different distribution results of the two types of braking will produce different braking effects,so in order to obtain good braking performance,it is of great significance to study the torque distribution control strategy.A good composite braking system should be able to fully recover the braking energy while ensuring the safety and stability of braking.However,there is a certain contradiction between the stability and recovery of the braking system,which can not reach the optimal state at the same time.Therefore,the paper proposes a multi-objective optimization algorithm to design and study the control strategy,and establishes a multiobjective optimization model according to the brake demand,and uses the standard non dominated sorted genetic algorithm-II(NSGA-II)to carry out the optimization analysis.For the decision-making problem of Pareto solution set obtained by optimization,an improved ideal solution method based on fuzzy control considering braking state is proposed.This method can consider the influence of multiple braking state parameters on the distribution of braking torque,and get the decision results more in line with the actual braking demand.The paper compared with two common weighting decisionmaking methods in Matlab environment.The results show that the decision-making method can consider the influence of vehicle braking state parameters and get more satisfactory output results.In the dissertation,the entire control strategy proposed in the Simulink-Cruise joint simulation environment is verified by joint simulation.The results show that the strategy can achieve the optimal torque distribution control and accurately reflect the impact caused by the braking state.However,due to the existence of multi-objective optimization process,the simulation time is long,it is difficult to realize the real-time optimal distribution of braking torque,and it cannot be applied to actual control.Therefore,the paper proposes a real-time allocation control strategy of "offline optimization and online allocation".Based on the theory of orthogonal experimental design,the multi-objective optimization and decision-making process is carried out offline by establishing an orthogonal table,and a discrete optimization look-up table is established.During online distribution,look-up table control distribution based on realtime braking status.Finally,the simulation is compared with the online optimization control strategy,and the average relative error of the output torque of each brake is calculated.The simulation time is 22 s,which greatly reduces the braking torque distribution control time,and the average relative error is less than 1%,which has extremely high accuracy.The results show that the control strategy proposed in the paper can realize the real-time optimal distribution control of torque,and the results can be applied to actual control,which has a certain engineering application ability. |
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