Key Technologies Research On Energy Management Problems Of Pure Electric Vehicles

As energy shortage and environmental degradation problems get increasingly serious, the development of new vehicles is attracting more and more attention from governments and industry.Under this background,pure electric vehicles with the merits of non-pollution and zero-emission become one of the most promising means of transportation.As limited energy supply system,pure electric vehicles' energy optimization and control shows extremely significant.Because of the application of power electronics and computer technology in automobile industry,energy management system of pure electric vehicles gets furtherly improved.However,people don't intend to fully tap the energy efficiency of vehicles,but just satisfy the basic accomplishment of energy management function.In fact,the energy management problem of pure electric vehicles involves a number of key technologies,improvement room for energy efficiency is considerable.And intelligent control theories and technologies provide an effective way to improve the key technologies aforementioned.Key technologies in pure electric vehicles energy management problems involve in three major aspects:1) design novel energy management strategy;2) seek accurate estimation methods of battery SOC;3) design effective regenerative braking control strategy.Among them,the problem of energy management strategy design can be summarized as a nonlinear dynamic optimization problem.It is a pity that there is still no mature solution for it,and need to absorb the existed research results in hybrid vehicles. As to the second aspect,power battery SOC estimation problem has the properties of nonlinear and high accuracy.The traditional linear methods have not met the actual estimated requirement.As to the third aspect,regenerative braking control strategy design should consider the practical factors like SOC constraint,etc,and need to be perfect. Therefore,combined with fuzzy control,neural network algorithm,the SVR algorithm and automobile brake theory,we study how to improve the key technologies of pure electric vehicles energy management in this paper.The main tasks are as follows.First of all,the background of the research and the status quo of pure electric vehicles at home and abroad are introduced,followed by the key technologies in the pure electric vehicles energy management strategies.Then,we focus on the significance,the status quo and the shortcomings in energy management strategies design,battery SOC estimation methods and regenerative energy recovery strategy design,respectively.Traditional pure electric vehicles have such problems as short drive mileage and poor accelerating performance.Aimed at them,we study the energy management control problems of new battery-supercapacitor dual-energy source of pure electric vehicles.First, based on the analysis of powers in energy storage system,the resistance powers during the vehicle's running and the constraints the energy storage system should obey,the mathematical model of energy management system is firstly established,whose objective functions are energy consumption ratio and acceleration time.Considering the nonlinear and dynamic properties during the electric vehicles travelling,fuzzy control algorithm is adopted for power distribution.In the distribution process,vehicles power demand, battery SOC and super-capacitor SOC are used as inputs,and battery power distribution factor as output.Compared to the look-up table strategy,vehicle acceleration performance and energy consumption rates get a greater improvement after adopting the fuzzy control strategy.It should be noted that,the decision of fuzzy rules relies on experience too much, and will inevitably be a local optimum.In recent years,the PSO algorithm with the advantages of global search gets a rapid development.Combined it with fuzzy control algorithm,the weakness of fuzzy controller is expected to overcome effectively. Therefore,an energy management fuzzy control strategy of dual-energy sources electric vehicles based on PSO is proposed subsequently.Experimental results show that,vehicle performance has been enhanced using the proposed control strategy.Obtaining accurate SOC of power battery is one prerequisite to achieve energy management optimal control of electric vehicles.Based on the influence factors analysis of SOC,neural network and support vector algorithms are used to estimate the SOC of power batteries,and give out a comprehensive evaluation about the estimated performance using the two algorithms aforementioned.Among them,neural network algorithms select the typical BP neural network and Elman neural network algorithmwhich has dynamic identification ability;while SVR algorithm using its two basic algorithms:ε-SVR algorithm andν-SVR algorithm.The results show that,all the four methods can get a good approximation to the actual value,and the average estimation error is less than 2%,while the estimation performance usingν-SVR algorithm is the best.Regenerative braking energy recovery is another key technology to improve the energy efficiency and extend the driving range of pure electric vehicles.Based on the analysis of security and regenerative energy,mathematic model of electric vehicle regenerative braking is established.Then,hydraulic proportional-adjustable valve distribution line of front and rear wheel is introduced to replace the ideal braking force distribution curve,and an improved regenerative braking energy distribution strategy is proposed.The experimental results show that,the proposed control strategy can effectively reduce the energy consumption of electric vehicles and improve the recovery of energy and energy efficiency.Followingly,among the existing brake control strategy, most don't consider the problem of battery anti-overcharging.So,a practical electric vehicle regenerative braking strategy that considering battery state of charge is proposed, and braking force distribution controller and regulator are designed respectively according to vehicle safety requirements and battery SOC constraint.Finally,the experimental results on ADVISOR simulation platform show that the vehicle obtains a better ability to prevent overcharging using the proposed strategy.As one important function of pure electric vehicles,energy management system needs to continuously improve and develop.Combined with related knowledge,this paper carry out further research on how to imorove and optimize the energy management technology from three aspects.The research results would be of great significance to enhance our country's pure electric vehicle research level and promote the process of industrialization.