Research On Monitoring And Warning System Of Fuel Cell Car

Aiming at the reliability and safety of fuel cell cars in operation,this thesis investigates the monitoring and warning system of fuel cell car.The thesis explores the vehicle monitoring system.According to the functional requirements,the parameters of the vehicle monitoring system are determined and the general scheme of the system is proposed.The system consists of the acquisition nodes and the communication nodes.Signals are transmitted between both nodes via serial ports.Specifically,the communication nodes transmit the signals from the vehicle monitoring system to the remote monitoring system through 4G devices.According to the general scheme,both the hardware and the software design of the vehicle monitoring system are well-settled,and the terminal of the vehicle monitoring system is fully completed.The thesis puts forward a warning algorithm for car rollover which has been verified through the off-line simulations.Taking the 3 degree of freedom(3DOF)rollover model as the reference,the lateral load transfer rate(LTR)is selected as the rollover evaluation standard and thereby,the time to rollover(TTR)can be estimated using the reference model and LTR rate.Further,in line with the predicted state,it is able to combine LTR and TTR to classify the rollover state,and then,provide an early warning of the car rollover.In details,this study establishes the whole vehicle model in Car Sim,fulfills the motor model and the rollover model in Matlab/Simulink environment,and at last,it integrates Car Sim and Matlab,and conducts offline simulations under three typical working conditions.The simulation results suggest that the proposed algorithm can accurately warn the situations of car rollover with low false alarms.The thesis completes the research on the electronic accelerator pedal fault diagnosis algorithm.After frequently appearing fault signals,the type and the cause of these faults are analyzed,this thesis designs an pedal fault diagnosis model based on the back-propagation neural network.The test results show the accuracy of pedal signal fault recognition reaches up to 99% and besides,the pedal fault code is given in terms of the on-board diagnostics(OBD)-II standard.Finally,this thesis presents the experiment of the vehicle monitoring system in the laboratory.Moreover,the feasibility of the system scheme and the system function are vertified.