A Charge Management System For Electric Vehicle Battery

Electric vehicles based on battery-powered are walked into our daily lives gradually.The charging technology of power batteries has become one of the main bottlenecks in the promotion of electric vehicles.Effective battery charging management strategies can improve the efficiency of charging and guarantee the safety of batteries and charging facilities as well.However,there are some limitations in traditional battery management system,such as homogeneous mode,fixed strategy of charging and poor communication between battery and charger.In this thesis,an adaptive charging management system based on the battery state,which consists of a battery-side charge management subsystem and a charger-side management subsystem is proposed for addressing the problems mentioned above.Real-time battery parameter collecting,battery status analysis,charging strategy adjustment and on-board diagnosis are implemented by the Microcontroller Unit of the battery-side charge management subsystem.At the same time,it can also communicate with the charger based on the national standard communication protocol and transmit charging parameters in real-time to help charger adjust the output power.On the other hand,the charger-side management subsystem includes the functions as follows:monitoring the output of the charger,parsing and responding to the message from the battery-side charging management subsystem.In this thesis,a power battery model based on the first-order RC circuits is built up firstly.Meanwhile,the parameters of the model are confirmed by HPPC test.We estimate the SoC by compromising the CC method and OCV method.The Extended Kalman Fittering and the Enhanced Coulomb Counting method are combined to realize online evaluation and regular correction of SoH.Secondly,according to the established battery model,we simulate the process of battery charging in the Simulink based on the three-stage charging strategy.And the results show that the increase of charging current for the total charging duration and the charging efficiency is not a global linear rise.Also,the unacceptable energy will be converted into heat energy and cause the higher battery temperature,which affects the battery life as well as charging safety.According to the simulation results,an on-line charging current optimization strategy based on battery state is designed in this thesis.The initial charging current and current optimization boundary are determined by the charge capacity,SoH and ambient temperature before charging in this strategy.Fuzzy adaptive controller(FAC)is used to adjust the charging current locally in real-time based on temperature transition rate of battery during the constant current stage.Finally,this thesis improves the traditional threshold comparison method,which is commonly used to diagnose battery charging safety faults with delay time,so that the threshold of faults and delay time can be adjusted according to the battery status.Through the actual charging test,the charging process under the charging management system which adopts the optimization strategy can keep the battery temperature stable.And the gain of total charging duration as well as total charging efficiency is improved.Additionally,it can also diagnose and respond to battery faults in time and guarantee the battery safety.The overall performance test results show that the system achieves the expected functions.It provides solutions to the problem of charge management technology for automotive power batteries in some way,which has significance of the promotion and application of current electric vehicles to some extent.