汽车滑行试验道路阻力和风阻系数不确定度分析

Uncertainties of Road Load and Air Drag Coefficient for Vehicle Coast down Test

摘要:

对汽车滑行试验过程中滑行速度进行统计学分析，发现各个轮次的滑行车速偏差近似与平均滑行车速呈线性关系。基于滑行车速，分别利用v-F方法和v-t方法拟合得到汽车的滑行阻力和风阻系数，分析其对应优化问题的凸性和滑行阻力、风阻系数的不确定度；结果表明，v-F方法对应拟合问题是凸的，而v-t方法对应的拟合问题是非凸的。在拟合道路载荷时，需要选择泛化能力较强的迭代算法，同时需要根据参数的物理意义，设置合理的初始值和约束边界，以便得到合理的拟合参数值和道路阻力；而且相比v-F方法，v-t方法得到的风阻系数不确定度更小，置信区间也更窄。另外，基于车辆滑行速度的统计规律，进行蒙特卡洛模拟，分别应用v-F和v-t方法，得到道路阻力和风阻系数近似为正态分布；结果表明，v-F方法会放大随机因素的影响，v-t方法得到的道路阻力和风阻系数均更为稳定。

关键词:汽车滑行道路阻力;风阻系数;随机过程;优化问题凸性;不确定度;蒙特卡洛模拟

Abstract:

The statistical analysis was performed to the vehicle velocity during coastdown test. It was found that the velocity deviation is approximately linear to the mean value. Based on the coasting velocity， the road load and air drag coefficient were fitted by v-t method and v-F method. At the same time， the convexity of corresponding optimization problem and the uncertainty of road load and air drag coefficient were analyzed. It was shown that fitting problem of v-F method is convex and that of v-t method is non-convex. During the fitting process， we need to choose the algorithm of high generalization capability and specify the initial values and bounds of parameters to obtain the reasonable fitting parameters and road load. Besides， the uncertainty of air drag coefficient is lower for v-t method and its confidence interval is narrower. At last， based on the statistical law of coasting velocity， the Monte Carlo method was applied to simulate the standard coast down test. It was found that the distribution of road load and air drag coefficient is approximately normal. And influence of randomness is highlighted for v-F method. The air drag coefficient and road load fitted by v-t method is more stable.

Key words:road load of coasting vehicle;air drag coefficient;stochastic process;convexity of optimization problem;uncertainty;Monte Carlo simulation