在汽车产业电动化和智能化进程中,汽车安全测试评价技术也从单纯被动安全向主被动安全融合方向延伸和扩展。本文从车内乘员保护、车外弱势道路使用者保护与主动安全三方面,深入对比分析了全球主流汽车安全测评规程的差异,总结了针对各...在汽车产业电动化和智能化进程中,汽车安全测试评价技术也从单纯被动安全向主被动安全融合方向延伸和扩展。本文从车内乘员保护、车外弱势道路使用者保护与主动安全三方面,深入对比分析了全球主流汽车安全测评规程的差异,总结了针对各测评工况的车辆安全开发技术要点,探讨了新能源与智能网联汽车安全测评规程的发展趋势。研究认为,主流汽车安全测评规程在被动安全评价方面越来越严格,主动安全测评工况比重在逐步增加,未来测评规程的发展重心将集中于主被动安全融合及针对复杂工况的虚拟测评两方面。此外,针对新能源汽车的电池安全测试已相对完善,未来研究重点可向电控系统测试、底盘稳定性测试和充换电设施与配套设备统一标准化认证等方向拓展;而构建合理、可靠的智能网联汽车OTA(over the air)测试、HMI(human machine interface)安全性和舒适性等测评方法,在中长期内将成为行业关注的重难点问题,且可借助自动驾驶模拟器等工具搭建虚实结合的复合测评体系。展开更多
A model-based estimator design and implementation is described in this paper to undertake combined estimation of vehicle states and tire-road friction coefficients.The estimator is designed based on a vehicle model wi...A model-based estimator design and implementation is described in this paper to undertake combined estimation of vehicle states and tire-road friction coefficients.The estimator is designed based on a vehicle model with three degrees of freedom(3-DOF) and the dual extended Kalman filter(DEKF) technique is employed.Effectiveness of the estimation is examined and validated by comparing the outputs of the estimator with the responses of the vehicle model in CarSim in three typical road adhesion conditions(high-friction,low-friction,and joint-friction roads).Simulation results demonstrate that the DEKF estimator algorithm designed is able to obtain vehicle states(e.g.,yaw rate and roll angle) as well as road friction coefficients with reasonable accuracy.展开更多
文摘在汽车产业电动化和智能化进程中,汽车安全测试评价技术也从单纯被动安全向主被动安全融合方向延伸和扩展。本文从车内乘员保护、车外弱势道路使用者保护与主动安全三方面,深入对比分析了全球主流汽车安全测评规程的差异,总结了针对各测评工况的车辆安全开发技术要点,探讨了新能源与智能网联汽车安全测评规程的发展趋势。研究认为,主流汽车安全测评规程在被动安全评价方面越来越严格,主动安全测评工况比重在逐步增加,未来测评规程的发展重心将集中于主被动安全融合及针对复杂工况的虚拟测评两方面。此外,针对新能源汽车的电池安全测试已相对完善,未来研究重点可向电控系统测试、底盘稳定性测试和充换电设施与配套设备统一标准化认证等方向拓展;而构建合理、可靠的智能网联汽车OTA(over the air)测试、HMI(human machine interface)安全性和舒适性等测评方法,在中长期内将成为行业关注的重难点问题,且可借助自动驾驶模拟器等工具搭建虚实结合的复合测评体系。
基金Project (Nos.50775096 and 51075176) supported by the National Natural Science Foundation of China
文摘A model-based estimator design and implementation is described in this paper to undertake combined estimation of vehicle states and tire-road friction coefficients.The estimator is designed based on a vehicle model with three degrees of freedom(3-DOF) and the dual extended Kalman filter(DEKF) technique is employed.Effectiveness of the estimation is examined and validated by comparing the outputs of the estimator with the responses of the vehicle model in CarSim in three typical road adhesion conditions(high-friction,low-friction,and joint-friction roads).Simulation results demonstrate that the DEKF estimator algorithm designed is able to obtain vehicle states(e.g.,yaw rate and roll angle) as well as road friction coefficients with reasonable accuracy.
