Research And Development Of Remote Diagnosis And Management System For Vehicle

As the result of great changes of structures of population and urban traffic, the number ofvehicle has seen a dramatic increase. Meanwhile, the traditional way of traveling, like walkingand by bike, have been replaced by Motor Vehicle, which results in serious environmental issues.To reverse these phenomena, Ministry of transport of the People`s Republic of China publishesrules and regulation about transportation of the12th five-year plan that some local governmentsdecide to carry out, bus urban, the project implementation.Obviously, it has great difference in maintaining standards between new energy buses anddiesel buses. Therefore, It requires a new system based on the relative existing technology tomonitor the information of various kinds of buses accurately，Timely and thus to Guarantee thesafety of buses.Remote diagnosis and management system for vehicle consists four parts: vehicle terminals,communication network, the user terminal and information center. Located in the bus, vehicleterminals aim to collect and transmit relevant data. The function of communication network is tomake sure the quality of transmitting of remote signal. The user terminal can supervise data ofvehicle through installing relevant application. Communication network is in charge of storageof vehicle. In future, a huge database will be built for the intelligent public transport system. Thispaper has completed research and developed the terminal of vehicle and its relevant software. Atthe same time, it has analyzed data from information center. The main work is described asfollow:(1) Based on the features of the vehicle failure and the mature technical development inthis field, select appropriate methods of data collection and transit model as well asdesign and construct the terminal of vehicles.(2) Construct the software of the terminal which can detect the data from the CAN bus inthe wi-fi environment.(3) Research in battery management system of Electric vehicles, Analysis the relationshipbetween battery remaining capacity and SOC estimate. Design Elman neural network inmatlab and chose the real data to test the effectiveness of the system.