随着社会发展及科学技术的进步，汽车工业在世界范围内迅速发展，使人们的生活更加便捷。汽车给人们生活提供方便的同时，也产生了一系列问题，如交通事故的发生、能源的消耗和环境污染，尤其在城市问题更为突出。为解决上述问题，国家大力推进新能源和智能驾驶汽车的发展，希望通过电动汽车的发展降低对传统能源的依赖及对环境的污染；同时通过智能驾驶，降低驾驶员劳动强度，避免疲劳驾驶或天气因素导致的安全事故。

本文基于分布式驱动电动汽车平台，开展智能驾驶纵向控制策略的研究，对实现车辆纵向运动驱动及制动等执行层的控制策略进行研究，主要开展工作为：

（1）基于模糊控制不依赖精确的数学模型的特点，模拟驾驶员模型，结合车辆纵向行驶工况分析，建立了基于模糊控制的多模式切换控制策略。该模式将车辆的运行工况分为巡航工况、接近工况、跟随工况和避撞工况，每一种工况下基于模糊控制开展控制策略设计，并建立了多模式切换的控制策略，实现车辆的巡航、接近、跟踪和避撞等功能随车间距、车速、加速度变化的稳定可靠切换，保证行车安全及道路利用率。

（2）基于电动汽车纵向控制的执行系统开展方案及控制策略设计。驱动系统设计时根据车辆动力性能需求确定分布式驱动的轮毂电机参数，确定驱动过程中采用扭矩控制方案；制动系统设计时，结合分布式驱动电动汽车四个车轮均可提供电机制动力的特点，确定前后轴制动力分配采用理想制动力分配曲线，在电机制动力与摩擦制动力分配时，充分考虑电机和蓄电池特性，同时结合车辆多模式纵向控制策略的控制要求，建立适合该车型的复合制动控制策略，在车辆纵向控制中保证行车安全、舒适的前提下进一步提升能量回收率。

（3）建立基于Matlab\Simulink和Carsim的联合仿真模型，通过制动系统的效能及典型工况下的能量回收率仿真分析验证控制策略可行性。

（4）结合常见纵向行驶的巡航工况、接近前车工况、跟随工况、避撞工况及综合工况开展仿真分析，验证纵向控制和复合制动控制策略在单一和综合工况下的适应性。

研究结果表明：本文设计的纵向控制策略及其执行系统可以很好的实现车辆的纵向控制需求，且车辆的安全性、舒适性和能量回收率均满足要求。

With the development of society and science, the automobile industry develops rapidly in the world, which makes people's life more convenient. While cars provide convenience for people's life, they also produce a series of problems, such as traffic accidents, energy consumption and environmental pollution, especially in cities. In order to solve the above problems, the state vigorously promotes the development of new energy and intelligent driving vehicles, hoping to reduce the dependence on traditional energy and environmental pollution through the development of electric vehicles; at the same time, through intelligent driving, reduce the labor intensity of drivers, and avoid safety accidents caused by fatigue driving or weather factors.

 

Based on the distributed drive electric vehicle platform, this paper carries out the research on the longitudinal control strategy of intelligent driving, and studies the control strategy of the implementation layer such as the longitudinal motion drive and braking of the vehicle. The main work is as follows.

 

(1)Based on the fact that fuzzy control does not rely on accurate mathematical model, a multi-mode switching control strategy based on fuzzy control is established by simulating the driver model and combining with the analysis of vehicle longitudinal driving conditions. In this mode, the vehicle operation conditions are divided into cruise condition, approach condition, follow condition and collision avoidance condition. In each condition, the control strategy is designed based on fuzzy control, and a multi-mode switching control strategy is established to realize the stable and reliable switching of vehicle cruise, approach, tracking and active collision avoidance functions with the change of vehicle spacing, speed and acceleration, so as to ensure the driving safety And road utilization.

 

(2) The drive and brake development plan and control strategy design of the executive system based on the longitudinal control of electric vehicles. In the design of the drive system, the in-wheel motor parameters of the distributed drive are determined according to the vehicle's power performance requirements, and the torque control scheme is adopted during the driving process; when the braking system is designed, combined with the characteristics that all four wheels of the distributed drive electric vehicle can provide electric power, Determine the ideal braking force distribution curve for the front and rear axle braking force distribution. When the electric mechanism power and friction braking force are distributed, fully consider the characteristics of the motor and battery, and combine the control requirements of the vehicle's multi-mode longitudinal control strategy to establish a compound system suitable for the model. The dynamic control strategy further improves the energy recovery rate under the premise of ensuring the safety and comfort of driving in the longitudinal control of the vehicle.

 

(3) A joint simulation model based on Matlab\Simulink and Carsim is established, and the feasibility of the control strategy is verified through the simulation analysis of the efficiency of the braking system and the energy recovery rate under typical working conditions.

 

(4) Carry out simulation analysis in combination with common longitudinal cruising conditions, approaching vehicle conditions, following conditions, collision avoidance conditions and comprehensive operating conditions to verify the adaptability of longitudinal control and compound braking control strategies under single and comprehensive operating conditions .

 

The results show that: the longitudinal control strategy and its implementation system designed in this paper can well meet the requirements of vehicle longitudinal control, and the vehicle safety, comfort and energy recovery rate meet the requirements.

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