Research On Key Technology In Operation Energy Efficiency Of Electric Vehicles Bus

The endurance mileage deficiency of EV is still the main obstacle which restricts the development of electric vehicle industry, so it is significant to improve the operation energy efficiency of electric vehicle in the case of limited vehicle energy. Especially when the electric city bus run at the city conditions of low speed and frequent brake, energy efficiency promotion space is more impressive.The key technology about operation energy efficiency of electric city bus mainly includes three parts:accurate estimation of battery SOC, efficiency optimization of driving motor and regenerative braking energy, JXK6121BEV type electric city bus is taken as study objects in this thesis, on the present level of battery and driving motor, the research is carried out around the above three contents, so as to realize the limited energy resources tapping and saving, in order to improve the energy utilization efficiency and prolong the endurance mileage of electric city bus, the main research contents are as follows:Calculate from substantial vehicle tests show that energy consumption ratio of the driving system is70.8%, base on the experimental of the energy loss in driving system, two methods including the efficiency optimization of motor drive system and regenerative braking energy are used to improve the energy utilization efficiency of electric city bus. The energy transfer efficiency from the grid to the wheels of electric city bus is analyzed, on this basis, the researches of efficiency in battery energy, efficiency of drive system and regenerative braking are studied. Efficiency test of driving motor is done under real measurement environment on an experiment bench for power train, which provide theoretical basis for efficiency optimization control of driving motor.In order to manage the vehicle power supply effectively, the battery management system including the structure, control system and software system was designed. Accuracy estimation of the battery SOC can improve the energy utilization efficiency of battery and extend the battery life, which is the key to energy management and braking force distribution. PSO-BP method was presented based on the testing of the battery performance, which used the battery voltage, charge-discharge rate and temperature as the input features parameters of neural network to estimate the battery SOC. The simulation results show that the presented method may estimate accurately the single battery SOC in the range of10%～90%. The estimation accuracy of battery packs SOC of the driving cycles of Chinese city buses was0.7%, and the estimation accuracy of the real vehicle battery packs was3.5%, which show that this method can meet the actual requirement.In order to improve the operation efficiency of driving system in electric city bus, the loss model of motor is established based on the vector control of induction motor, and simulation model of efficiency optimization control system based on loss model is established in MATLAB/Simulink. Aiming at drawbacks that efficiency optimization control precision is being dropped while motor parameters change in loss model control strategy, a hybrid method in motor efficiency optimization control is proposed, that is the loss model is used to determine the optimal flux search range, which can shorten search time, and then generalized regression neural network is used to search the optimal flux, which decrease the effect of motor parameters on efficiency optimization and improve the control precision. Comparison simulation experiments of the two efficiency optimization methods are carried out in MATLAB/Simulink, the motor efficiency with non-optimum is62.95%, and the optimized efficiency are respectively84.23%and86.72%based on the loss model optimization and the hybrid method when the given speed and torque are1003r/min/200N.m. and in the condition of1691r/min/619N.m, the non-optimum efficiency is75.86%, and the optimized efficiency are respectively80.44%and81.56%. In order to validate the practicality of efficiency optimization control strategy, the real vehicle condition simulation experiment is done, and the non-optimum efficiency is59.93%, the optimized efficiency are respectively82.45%and84.92%. The simulation experiment results show that the robustness, practicality and accuracy of hybrid method is better than the method based on loss model.In order to recover the energy regenerated in frequent braking, the braking force distribution control is researched. It is difficult to build the actual mathematical model for the brake force distribution which is affected by the speed, braking intensity and battery SOC, The fuzzy control strategy for braking force distribution is developed, and the simulation model of brake force distribution is established in Simulink. The electric city buses model is established by cruise and co-simulated with MATLAB. For the typical driving cycles of city buses in China, the driving distance within a cycle is5.8km, the battery SOC decreased0.376%by the fuzzy control strategy for braking force distribution, the endurance mileage of the90%DOD increased10.2km and it improved by7.8%. For the FTP cycles in American, the driving distance within a cycle was16.84km, the battery SOC decreased by1.487%based on the fuzzy control strategy for braking force distribution, the endurance mileage of the90%DOD increased9.8km and it improved by8.84%. The experiment results show that the method can improve the energy efficiency effectively, recover the regenerative braking energy in maximum scale, extend the endurance mileage of electric city bus and avoid overcharge effectively.