基于预见性巡航的重型卡车质量估计系统设计

为了满足预见性巡航控制（Predictive Cruise Control, PCC）系统对重型卡车质量的精度要求，针对传统重型卡车质量估计算法的不足，设计了重型卡车的质量估计系统。开发了基于车辆纵向动力学和基于高精度地图的卡车质量估算策略，采用归一化最小均方算法（Normalized Least Mean Square, NLMS）对估计质量进行了平滑性处理；完成了质量估计系统的硬件设计；搭建了质量估计算法的Simulink模型，采用基于模型设计的方法进行了系统软件的开发；实车验证了整个系统的可靠性以及质量估计算法的精确性。试验结果表明:与实际的卡车质量相比，质量估计系统计算得到的卡车质量的误差在9%以内。

Design of the mass estimation system for heavy truck based on predictive cruise

To meet the accuracy requirements of PCC system on heavy truck mass, a mass estimation system for heavy trucks was designed because of the shortcomings of the traditional heavy truck mass estimation algorithms. The mass estimation algorithm which was based on the longitudinal dynamics model of vehicle and high-precision map was developed. NLMS algorithm was employed to smooth the mass which was estimated. The hardware design of the mass estimation system was completed. Simulink strategy model was built, and the system software was developed using model-based design method. The reliability of the entire system was verified and the accuracy of the mass estimation strategy was verified by real vehicle. The test results show that the error is within 9% compared the truck mass which the mass estimation system calculated with the actual truck mass.