Research On Energy Management Strategy Optimization And Extender Control System For Extended Range Electric Vehicle

Environmental pollution and energy crisis are major challenges for the development of automobile industry in China.There is a consensus among China government,auto companies and research institutions that developing energy-efficient and new-energy vehicle is an efficient way to achieve the adjustment of automobile industry,and "all electric drive" is considered as the development direction.Extended range electric vehicle(EREV)has the advantages of lower cost,unlimited driving range,more clean,high efficiency and without complex mechanical transmission device,and thus it is a good choice for the automobile industry in China.Based on global optimization,this paper deeply studied vehicle model construction,energy management strategy design and optimization,and extender control system design.A forward EREV simulation model was constructed based on MATLAB/Simulink software.This simulation model includes four parts:system dynamic model(traction motor model,extender system model,Li-battery model),driving dynamic model,driver model,and vehicle control unit model.Mean value model of Miller cycle engine is included in extender system model,and the mean value model is based on an intake timing valve correction factor.The bench test and vehicle test were developed to validate the model control performance.Simulation results show that the proposed forward simulation model could better reflect the system state under the real cycle,it could serve as simulation platform to support energy management strategy(EMS)develop and extender control system design.The global optimization problem of EREV energy flow was researched.The dynamic programming algorithm was adopted to solve the global optimization problem of energy flow,and the optimization target was the minimum of fuel consumption.Since dynamic programming has numeric problem with interpolation,a modified dynamic programming(ESR DP)algorithm based on effective solving region(ESR)in battery state of charge(SOC)state space was proposed.Simulation results show that the ESR DP algorithm could reduce the accumulated error compared to classic DP algorithm,it also made the difference between battery final SOC value and target value less than 1%.Meanwhile,ESR DP algorithm could improve fuel economy about 19%in NEDC cycle compared to CD/CS strategy(charging depleted/charging sustained),which was adopted by original vehicle.EREV charging characteristics was systematic analyzed.There were two control objectives for EMS to improve EREV fuel economy of the whole driving life:the vehicle required power should be optimized allocated in driving period,and to control battery SOC decreasing in an approximately linear manner with the extension of driving distance;in order to improve battery's ability to store more electricity as EREV finishes its trip and arrives at charging station,battery SOC should reach its low threshold.Thus,the control model set was generated by Elman Neural Network,which was adopted to train the control rules of global optimal EREV energy flow.Coupling the control model set,battery energy consuming rate calculation module,target SOC calculation module and control model selection module,a real-time energy management strategy based on the control model of global optimal EREV energy flow was proposed.In order to improve extender dynamic performance in the process of responding to target generated power,the extender control system was designed based on V shape development mode.For the software in control system,an extender coordinated control strategy was proposed based on fuzzy adaptive PID controller,in which the basic parameters of PID controller was optimized by Generic Algorithm.A fuzzy reasoning algorithm,whose inputs was extender speed and its changing rate,was proposed.In terms of the hardware in control system,the selection of microprocessor,power circuit and communication module design was completed,and the overall design of printed circuit board was completed using Altium Designer.Finally,an of extender coordinated control strategy was developed by MATLAB automatic code generation technology,and the embedded C code was integrated with the underlying driver code and was loaded into the hardware of extender controller.A hardware-in-loop test for EREV vehicle control unit was established by dSPACE real-time simulation system.Through the hardware in the loop test,the control performance and energy saving effect of real-time energy management control strategy were verified.The analysis of test results show that the EMS could download in vehicle control unit hardware and could achieve the design goals;and when the target driving distance information was known,the fuel economy could be improved for about 9.2%by adopting the proposed EMS compared with the original vehicle control strategy.Meanwhile,the battery SOC could be dropped to lower threshold as EREV reaching charging station.Extender test bench was set up,and several extender working mode tests were carried out.The analysis of test results showed that the extender control system could control extender in real-time and achieve the design goals.In terms of extender start-up bench test,compared with the start-up strategy based on generator speed control,the proposed start-up strategy based on generator torque control could reduce the vibration acceleration at least by 68.9%;For extender generating mode test,the coordinated control strategy based on fuzzy adaptive PID controller could improve the dynamic performance and steady performance,in terms of overshoot and steady state error,it could decrease for 55.0%and 36.0%respectively,compared with the required performance index value.