In order to achieve the improvement of the driving comfort and energy efficiency,an new e-CVT flexible full hybrid electric system(E2FHS) is proposed,which uses an integrated main drive motor and generator to take the place of the original automatic or manual transmission to realize the functions of continuously variable transmission(e-CVT).The design and prototype realization of the E2FHS system for a plug-in hybrid vehicle(PHEV) is performed.In order to analyze and optimize the parameters and the power flux between different parts of the E2FHS,simulation software is developed.Especially,in order to optimize the performance of the energy economy improvement of the E2FHS,the effect of the different energy management controllers is investigated,and an adaptive online-optimal energy management controller for the E2FHS is built and validated by the prototype PHEV.
A combined algorithm for battery state of charge(SOC)estimation is proposed to solve the critical issue of hybrid electric vehicle(HEV).To obtain a more accurate SOC,both coulomb-accumulation and battery resistance-capacitor(RC)model are weighted combined to compensate the deficiencies of individual methods.In order to solve the key issue of coulomb-accumulation,the battery thermal model is used.Based on the principle of energy conservation,the heat generated from battery charge and discharge process is converted into the equivalent electricity to calculate charge and discharge efficiency under variable current.The extended Kalman filter(EKF)as a closed loop algorithm is applied to estimate the parameters of resistance-capacitor model.The input variables do not increase much computing difficulty.The proposed combined algorithm is implemented by adjusting the weighting factor of coulomb- accumulation and resistance-capacitor model In the end,four different methods including Ah-efficiency,Ah-Equip,RC-SOC and Combined-SOC are compared in federal testing procedure (FTP)drive cycle.The experiment results show that the proposed method has good robustness and high accuracy which is suitable for HEV application.
