Design Of Distributed Lithium-ion Battery Management System

With the increasing ownership of global cars,environmental pollution and shortage of resources are becoming increasingly prominent.The dependence of traditional automobile on oil resources is increasing year by year.The rise and development of new energy vehicles reveals that people from starting realize to develop and use the importance of clean energy.The state and the government also introduced a series of policies to promote energy-saving and new energy automotive industry development,puting forward to support the development of electric vehicles,fuel cell vehicles,promoting self-owned brand of energy-saving and new energy vehicles to achieve international standards.As a key factor to restrict the development of electric vehicles and the power source of the motor vehicle,the battery performance is directly related to the length of the vehicle mileage,service life and safety.A reasonable set of battery management system(Battery Management System,BMS)can monitor the status of lithium-ion battery,evaluate the whole vehicle's safety,complete man-machine interface communication and ensure reasonable,safe and efficient of energy using when electric vehicles in the operation process.So it is very important to establish a set of reasonable and reliable distributed battery management system,and it is worth to estimate the Charge of State(SOC)of the lithium-ion battery by using a suitable algorithm.For the research of the SOC estimation,this paper finally chooses particle swarm PSO(Particle Swarm Optimization)(Back Propagation)to optimize the BP neural network algorithm to estimate the SOC lithium ion battery through the analysis of advantages and disadvantages of the traditional estimation method and measure the feasibility and accuracy of various estimation methods.By designing working conditions,which conducting emulation proof of SOC by using two algorithms in MATLAB.The results show that the PSO-BP algorithm is more reliable and accurate than the BP algorithm.At the end of the paper,it succeed to obtain the algorithm code that can stable operate in DSP by using C code transplant technology.In addition,this thesis also completed the design of the distributed BMS master control board with TMS320F28335 as the control core,integrated IO isolated output circuit,AD acquisition circuit,SPI communication circuit,CAN communication circuit and so on,which realized the combination of the main control board,the acquisition board and the upper computer,as well as designed a set of reasonable distributed BMS.