【作者】 柏睿；

【导师】 崔胜民；

【作者基本信息】 哈尔滨工业大学 ， 车辆工程， 2010， 硕士

【摘要】 面对有限的石油资源和日趋严重的环境污染,汽车的发展不得不寻找新的替代技术。电动汽车凭借着尾气零排放的优越环保性能,电能来源广泛,能量利用率高,噪声低等优点,近来得到了广泛的关注。世界各国都对电动车的开发投入了大量的人力物力,我国电动汽车的开发也得到了国家的大力扶持。面对目前纯电动汽车电池昂贵,续驶里程短的问题,开发以太阳能电池作为辅助能源电动汽车不失为一个有效的解决方法。本课题针对太阳能辅助的电动汽车的驱动系统进行了设计。根据整车性能要求,选用永磁无刷直流电机作为车辆的驱动执行机构,将电机进行轮内安装构建四轮驱动系统。针对采用此四轮驱动的电动汽车,构建了四轮驱动的电子差速控制方法,同时对所用永磁无刷直流电机的控制系统进行了设计。本文采用ADAMS建立整车模型,仿真获取了实验道路条件下电动汽车各个车轮在不同车速和转向角度下的转速离散数据。基于BP神经网络,对离散数据进行拟合,构建了神经网络模型,即实验道路条件下的四轮电动车差速的主控制模型。采用滑移率检测作为差速的辅助控制环节,对车轮的实际状态进行反馈调节,扩展了电子差速控制系统适应性。采用BP神经网络进行差速预测滑移率检测反馈,避免了传统基于Ackerman转向数学模型计算的转速调节电子差速系统输出过于理想化的问题。永磁无刷直流电机采用转速电流双闭环反馈控制,并对调速环的参数进行计算确定。在MATLAB/Simulink模块中建立电机和差速系统的模型,所建差速控制系统的仿真结果表明电子差速系统能够根据控制参数进行良好的控制。更多还原

【Abstract】 Confronted with limited oil natural resources and the growing problem of environmental pollution, vehicle has to develop a new replaceable technology to solve all the problems. As one of the solutions, Electric Vehicle has attracted broad attention because of its advantages of wide energy income, high efficiency, low noise, superior zero-emission environmental performance and so on. Many countries have put in big effort in the development of Electric Vehicles, so is our country. But there are some shortcomings for pure electric cars, such as low battery capacity and short driven mileage. The development of electric vehicle with solar cells as a supplemental energy source can be regarded as a reasonable way.A drive system was designed for electrical vehicle in this thesis. According to the requirement of vehicle performance, BLDCM was selected as the vehicle driven actuator. The BLDCMs were installed in wheel in order to build the 4-wheel driven system. Regarding to driven system designed, electrical differential system and motor control system were constructed.Using ADAMS software, the whole vehicle model was built to obtain discrete dates of the wheels’rotating speeds under the testing road conditions. Based on BP neural network, these dates obtained were fitted to make up neural networks. The slip ratio detection is regarded as assistance control block. Compared with general differential system using rotating speed controlling, the new differential system can avoid the problem effectively that Ackerman steering mathematical model always idealize the differential outputs. The BLDCM control takes wheel rotating speed and current as feedback and the parameters of the control system has been settled.Simulation results showed that the electrical differential system works well according to the inputs.更多还原