Abstract
The dynamic parameter allocation of the suspension system has an important influence on the comprehensive driving performance of the tracked vehicle. Usually, the allocation of suspension parameters is based on a single performance index, which has the disadvantage of not being able to achieve multi-performance optimization. Therefore, a novel optimization method using multi-performance index-oriented is presented. Firstly, considering the vertical vibration excitation caused by road roughness, the input (excitation) model of road roughness is embedded to establish the parametric dynamic model of the tracked vehicle. Then, the evaluation index and its quantitative algorithm, which reflect the multi-aspect performance of the suspension system, are proposed. Moreover, the parameter allocation objective function based on multi-index information fusion is designed. Finally, two allocation optimization methods are presented to solve the parameter allocation, i.e., equal weight allocation and expert knowledge-based weight allocation. By comparing the results obtained by the two methods, it is found that the performance of the suspension system can be improved effectively by optimizing the parameters of suspension stiffness and damping. Furthermore, the optimization of weight allocation based on expert knowledge is more effective. These provide a better knowledge reference for suspension system design.
Highlights
Tracked vehicles are designed to move on rugged off-road terrain, such as military combat tanks [1]. ese vehicles have strong off-road maneuverability and ensure the vehicle’s ability to pass under extreme road conditions [2, 3]. e suspension is an important part of tracked vehicles, which improves the operator’s endurance to withstand the transmitted shock and vibration
Based on the tracked vehicle road roughness input model and parameterized dynamics model, the evaluation indexes reflecting the multiple aspects of performance of the tracked vehicle suspension system and their quantization algorithm are analyzed and expounded. en, the objective function of parameter allocation based on multi-index information fusion is designed to realize the optimal allocation of dynamics parameters of the tracked vehicle suspension system
According to the objective function designed in step 1, the value range of parameters such as stiffness and damping of the suspension system is determined, and a reasonable optimization algorithm is introduced for the iterative solution to obtain the optimal solution of the objective function of each index
Summary
Tracked vehicles are designed to move on rugged off-road terrain, such as military combat tanks [1]. ese vehicles have strong off-road maneuverability and ensure the vehicle’s ability to pass under extreme road conditions [2, 3]. e suspension is an important part of tracked vehicles, which improves the operator’s endurance to withstand the transmitted shock and vibration. To overcome the influence from the distribution of the suspension dynamics parameters (stiffness and damping), it is necessary to design a dynamic parameter allocation optimization method of tracked vehicle multi-axle suspension. En, the objective function of parameter allocation based on multi-index information fusion is designed to realize the optimal allocation of dynamics parameters of the tracked vehicle suspension system. The distribution of suspension stiffness and damping parameters of each axle is nonuniform Their specific allocation value is often determined based on experience and lack of theoretical basis. Irdly, based on the results of parameter allocation optimization, the suspension performance of the tracked vehicle traveling on different roads at different speeds is compared and analyzed, and an effective method for the allocation optimization of suspension system stiffness and damping parameters is verified.
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