In this paper, a novel piecewise affine (PWA) modeling framework and a hybrid optimal control scheme based on the developed PWA model for the intelligent vehicle longitudinal dynamics are proposed. The proposed methodology approximates the nonlinear characteristics of the system major components, i.e. the engine, the automatic transmission and the tire, using the PWA representation method firstly. Due to the affine submodel switching behaviors of the PWA model and the fact that the intelligent vehicle must be worked in two discrete modes (driving and braking) for regulating the longitudinal velocity automatically, the control procedure of the intelligent vehicle longitudinal dynamics actually shows a hybrid nature with both continuous variables and discrete events. Thus, to further solve the system hybrid control problem, the intelligent vehicle longitudinal dynamics whose major components are modelled in the PWA form is further transformed into a computational mixed logical dynamical (MLD) model in this work, based on which a hybrid model predictive control (HMPC) strategy, which can simultaneously calculate the switching sequences of the intelligent vehicle longitudinal working modes (binary control inputs) and the throttle angle and braking pressure (continuous control inputs) during autonomous velocity regulation, is designed by solving a mixed-integer quadratic programming (MIQP) problem. Simulation and experimental results are finally provided to verify the superior control performance of the designed hybrid controller in longitudinal velocity regulation under typical driving conditions.

在本文中，提出了一种新颖的分段仿射 (PWA) 建模框架和基于开发的 PWA 模型的混合优化控制方案，用于智能车辆纵向动力学。所提出的方法首先使用PWA表示方法来逼近系统主要部件，即发动机、自动变速器和轮胎的非线性特性。由于 PWA 模型的仿射子模型切换行为以及智能车辆必须在两种离散模式（驱动和制动）下工作以自动调节纵向速度的事实，智能车辆纵向动力学的控制过程实际上显示了混合动力具有连续变量和离散事件的性质。因此，为进一步解决系统混合控制问题，在这项工作中，将主要部件以 PWA 形式建模的智能车辆纵向动力学进一步转化为计算混合逻辑动力学 (MLD) 模型，在此基础上，混合模型预测控制 (HMPC) 策略可以同时计算切换通过求解混合整数二次规划 (MIQP) 问题，设计了自主调速过程中智能车辆纵向工作模式（二进制控制输入）和节气门角度和制动压力（连续控制输入）的序列。最后通过仿真和实验结果验证了所设计的混合控制器在典型驾驶条件下纵向调速的优越控制性能。