The Design Of Vehicle Alternator's Synthetic Experiment System Based On CAN Bus

The Controller Area Network (CAN) is a serial, asynchronous, multi-master communication protocol for connecting electronic control modules, sensors and actuators in automotive and industrial applications. In this paper, we introduce CAN bus into vehicle alternator's experimental testing system. By using this experimental hardware platform and testing software we can emulate alternator's actual working situation and gain alternator's performance data and figures. By analyzing these performance data we can accomplish the evaluation on the quality of the vehicle alternator. In this paper we also establish vehicle alternator's fault diagnosis system. This fault diagnosis process has two main steps. The first fault diagnosis step is extracting faults symptoms. We use sensors to get alternator's electric data by CAN bus and do our best to find out the relations between alternator's electric faults and fault symptoms. The second fault diagnosis step is the use of inference method. We integrate fault diagnosis system with fuzzy and neural networks theories and establish fuzzy rule-based knowledge frame by experts for training neural networks. Thus we build a real-time and automatic fault diagnosis system by using fuzzy neural networks. At last, we simulate fuzzy neural networks fault diagnosis by Matlab's Neural Networks Toolbox. The simulation results show the validity and practicability of this fault diagnosis system in our paper.