电动车自适应巡航控制方法研究

发布时间：2019-06-26 15:13

【摘要】：随着全球经济和汽车电子技术的迅猛发展,汽车的产销量急剧增加,但是这也带来了交通拥堵、交通事故频发、环境污染严重以及能源消耗量急剧增加等一系列社会问题。为了解决以上社会问题,电动车以及车辆的主动安全技术成为当今汽车技术的发展方向。自适应巡航控制(Adaptive Cruise Control,ACC)作为安全辅助驾驶技术,是车辆主动安全技术的一个重要组成部分,已成为国内外研究的热点。然而关于自适应巡航系统的研究目前多集中于燃油车,对电动车的研究较少。又因为自适应巡航系统的研究方法也随着车辆动力系统的变化而变化,因此本文对基于电动车的自适应巡航系统的研究有较大的实际意义与价值。本文采用分工况、分层的策略对电动车的自适应巡航系统进行控制算法研究。将控制系统分为决策层与执行层:根据ACC车辆的行车环境,将决策层分为跟踪控制、速度控制和匀速控制三种模式;执行层分别设计驱动控制器和制动控制器,实现对决策层输出的期望加速度的跟踪控制。首先,本文建立了决策层跟踪控制模式下的控制对象模型。跟踪控制模式主要实现ACC车辆与目标车辆的实际车间距对期望安全车间距的跟踪。首先选择两车期望安全间距的规划策略,完成ACC车辆与目标车辆之间安全车间距的规划;当车辆进入弯道行驶时,需要将雷达获得的两车径向相对运动状态信息转换为两车的纵向相对运动信息,进而对ACC车辆进行纵向控制;最后仅考虑ACC系统的纵向控制,结合ACC车辆与目标车辆之间的纵向运动学特性与规划的期望安全车间距,建立两车车间距误差LPV模型。其次,设计了ACC系统决策层控制策略,包含ACC车辆在不同工况下的控制模式以及在各个控制模式下控制器的切换策略,实现控制器的平滑切换。在跟踪控制模式下,由于已建立的车间距误差LPV模型的参变量可测并且有界,故可使用H?控制算法设计间距控制器。针对速度控制模式,使用PID控制算法设计速度巡航控制器,实现对驾驶员设定速度的跟踪。最后,建立了执行层的驱动控制器和制动控制器,实现对决策层输出的期望加速度的跟踪。由于电动车可以实现对车轮扭矩的精确控制,故可通过车轮扭矩来控制车辆的驱动和制动过程。在建立ACC车辆的纵向驱动动力学模型和制动动力学模型时,考虑车辆滑移率以及前后轴载荷转移的影响,并由于该模型的强非线性,可使用滑模控制算法设计驱动控制器和制动控制器。在目标车辆减速、目标车辆先减速后加速、目标车辆急刹车、相邻车道车辆插入等工况下,用高精度仿真软件veDYNA对由决策层与执行层的控制器组成的ACC系统进行仿真验证。仿真结果表明,设计的ACC算法控制效果良好,具有较强的鲁棒性。
[Abstract]:With the rapid development of global economy and automobile electronic technology, the production and sales of cars have increased sharply, but this has also brought a series of social problems, such as traffic congestion, frequent traffic accidents, serious environmental pollution and a sharp increase in energy consumption. In order to solve the above social problems, electric vehicles and vehicle active safety technology has become the development direction of automobile technology. Adaptive cruise control (Adaptive Cruise Control,ACC), as a safety auxiliary driving technology, is an important part of vehicle active safety technology, and has become a hot research topic at home and abroad. However, the research on adaptive cruise system is mostly focused on fuel vehicles, but the research on electric vehicles is less. Because the research method of adaptive cruise system also changes with the change of vehicle power system, the research of adaptive cruise system based on electric vehicle has great practical significance and value in this paper. In this paper, the control algorithm of adaptive cruise system of electric vehicle is studied by using the strategy of dividing working conditions and layering. The control system is divided into decision layer and execution layer: according to the driving environment of ACC vehicle, the decision layer is divided into three modes: tracking control, speed control and uniform speed control, and the driving controller and braking controller are designed respectively to realize the tracking control of the expected acceleration of the output of the decision layer. Firstly, the control object model in decision layer tracking control mode is established in this paper. The tracking control mode mainly realizes the tracking of the actual workshop distance between the ACC vehicle and the target vehicle to the expected safety workshop distance. Firstly, the planning strategy of the expected safety distance between the two vehicles is selected to complete the planning of the safety workshop distance between the ACC vehicle and the target vehicle. When the vehicle enters the bend, the radial relative motion state information obtained by the radar needs to be transformed into the longitudinal relative motion information of the two vehicles, and then the longitudinal control of the ACC vehicle is carried out. Finally, considering only the longitudinal control of ACC system, combining the longitudinal kinematic characteristics between ACC vehicle and target vehicle and the planned expected safety workshop distance, the LPV model of two-car workshop distance error is established. Secondly, the decision layer control strategy of ACC system is designed, which includes the control mode of ACC vehicle under different working conditions and the switching strategy of controller under each control mode, so as to realize the smooth switching of the controller. In the tracking control mode, the parameters of the established workshop distance error LPV model can be measured and bounded, so H? The distance controller is designed by the control algorithm. Aiming at the speed control mode, the speed cruise controller is designed by using PID control algorithm to track the speed set by the driver. Finally, the driving controller and braking controller of the executive layer are established to track the expected acceleration of the output of the decision layer. Because the electric vehicle can realize the accurate control of the wheel torque, the driving and braking process of the vehicle can be controlled by the wheel torque. When establishing the longitudinal drive dynamics model and braking dynamics model of ACC vehicle, the influence of vehicle slip rate and front and rear axle load transfer is taken into account. Because of the strong nonlinear of the model, the sliding mode control algorithm can be used to design the drive controller and braking controller. Under the conditions of deceleration of the target vehicle, deceleration and acceleration of the target vehicle, brake of the target vehicle and insertion of the adjacent lane vehicle, the ACC system composed of the controller of the decision layer and the executive layer is simulated and verified by using the high precision simulation software veDYNA. The simulation results show that the designed ACC algorithm has good control effect and strong robustness.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U469.72;TP273

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