基于代理模型进化的履带车辆动力学参数优化

为解决履带车辆动力学优化过程因代理模型构建和应用的不足而导致的参数寻优精度和效率不高的问题，提出基于代理模型进化的参数优化方法，将优化迭代和代理模型动态构建相融合，来降低仿真模型调用次数和提高优化效率。根据车辆几何拓扑结构，构建考虑履带包络效应的车辆多体动力学模型；提出优化设计变量空间的3层子空间划分方法，以及具有空间聚焦、空间约简和跳出局部寻优的多级模糊聚类空间约简方法，实现设计参数在3层子空间的高效缩减。以履带车辆多体动力学模型参数优化过程为例进行应用验证。研究结果表明：在3种路况下的履带车辆多体动力学优化过程降低仿真模型调用次数最高可达85%;表征履带车辆行进特性的综合性能指标分别提升约32.4%、24.5%、20.4%。证明了新方法可有效提高动力学模型的优化效率和精度。

Dynamics Parameter Optimization for Tracked Vehicle Based on Surrogate Model Evolution

To solve the problem of low precision and low efficiency in tracked vehicle dynamics optimization resulting from the weaknesses of traditional agent model construction and application, a parameter optimization method based on surrogate model evolution is proposed. It integrates the optimization iteration process with the dynamic construction process of the surrogate model to reduce the times of invoking the simulation model and hence improve the optimization efficiency. First, based on the vehicle’s geometric topology, a multi-body dynamics model considering track envelope effect is constructed. Then, the design space is divided into three-level subspaces. A multi-level fuzzy clustering space reduction method with spatial focus and spatial reduction and not bounded by local optimization is proposed to efficiently reduce the design parameters in the three-level subspaces. Finally, the application is verified by taking the parameter optimization process of the tracked vehicle’s multi-body dynamics model as an example. The results show that the multi-body dynamics optimization process of the tracked vehicle under three road conditions reduces the invoking times of simulation model by up to 85%; the comprehensive performance indexes representing tracked vehicle ride comfort and firing accuracy are increased by about 32.4%, 24.5% and 20.4%, respectively. It is proved that this method can effectively improve the efficiency and accuracy of dynamic model optimization.