Development and Implementation of Electric Vehicles

• Main Authors: Shih-Yu Wu, 吳士瑜
• Other Authors: Ming-Shyan Wang
• Format: Others
• Language: zh-TW
• Published: 103
• Online Access: http://ndltd.ncl.edu.tw/handle/92411660547828735599

碩士 === 南台科技大學 === 電機工程系 === 102 === Comparing with traditional dc motors and induction motors, brushless dc motors (BLDCMs) provide the merits of no brushes, low consumption, low volume, better stability and larger torque. As a result, BLDCMs are popular in industrial automation systems. Generally, the drives with pulse-width modulated inverter are used in the motor control system. In order to get smooth and stable output torque, the Hall-effect sensors are employed to sense the rotor position for commutation so that the common six-step driving algorithm will be applied to the system. Proportional-Integral-Derivative (PID) control is the widest algorithm used in control systems. But it is difficult to tune its gains at various conditions. In this thesis, self-tuning neural network control is considered to assist the PID control for gain tuning in a short period. The experimental results are first provided to verify the correctness of self-tuning neural network plus PID control for 400W-motor control systems in the thesis. Secondly, an electric vehicle is set up for applications. This electric vehicle includes two sets of the designed motor systems and CAN BUS transmission that it can move the straight line and curve paths.