Abstract: The adaptive cruise control (ACC) strategy based on real-time estimation of road slope was proposed to address the issue of insufficient control accuracy and safety in vehicle ACC systems under ramp driving conditions. The algorithm adopted a hierarchical control structure, dividing the ACC system into upper controller and lower controller. The upper controller employed PID controller and linear quadratic regulator (LQR) to calculate the expected acceleration, and the lower controller utilized the unscented Kalman filter (UKF) algorithm for road slope estimation. Based on the longitudinal dynamics of the vehicle, considering the impact of road slope changes, the expected acceleration was converted into the corresponding throttle opening and brake pressure to achieve vehicle cruise and following functions. The feasibility of the proposed ACC system strategy was verified through MATLAB/Simulink and Carsim co-simulation and compared with traditional control strategies. Simulation results demonstrate that compared to traditional control strategies, the improved ACC system control strategy can accurately identify road gradients and has better control accuracy and safety under ramp driving conditions.

Key words: vehicle engineering; adaptive cruise control; road slope estimation; unscented Kalman filter; linear quadratic regulator

摘要： 针对汽车自适应巡航控制(adaptive cruise control, ACC)系统在坡道行驶工况下控制精度和安全性不足问题，提出基于道路坡度实时估计的自适应巡航控制策略。算法采用分层式控制结构，将ACC系统分为上层控制器和下层控制器，上层控制器采用PID控制器和线性二次型调节器(linear quadratic regulator, LQR)计算期望加速度；下层控制器利用无迹卡尔曼滤波(unscented kalman filter, UKF)算法对道路坡度进行估计，以车辆纵向动力学为基础，考虑道路坡度变化的影响，将期望加速度转换为对应的节气门开度和制动压力，以实现车辆巡航和跟随功能。通过MATLAB /Simulink与Carsim联合仿真验证ACC系统控制策略的可行性，并与传统控制策略进行对比分析。仿真结果表明：在坡道行驶工况下，改进后的ACC系统控制策略相比于传统控制策略，能够精准识别道路坡度，具备较好的控制精度和安全性。

关键词: 车辆工程；自适应巡航控制；道路坡度估计；无迹卡尔曼滤波；线性二次型调节器