Optimized determination of vehicle durability test specification correlated with user-targeted fatigue life using the multi-index decision-making approach

To address the development of vehicle structure durability test specification linked to user’s targeted fatigue life, a novel method is proposed that combines the multi-objective genetic algorithm with CRITIC-TOPSIS multi-index decision-making approach. Firstly, based on pseudo-damage theory, the vehicle’ damage is calculated under different driving conditions and then the damage-equivalent model of the “user-test site” is constructed. Then, NSGA-II algorithm is employed to solve it and the CRITIC-TOPSIS method is applied to obtain an integrated optimal solution considering the inclusion of several decision indexes. Finally, evaluation against traditional least squares method (LSM) demonstrates the effectiveness. Results show that the determined optimal test cycles effectively address the issue of excessive dispersion observed in solutions of LSM, ensuring a balanced reproduction of target damage for each vehicle part. Besides, the mean value and standard deviation of relative pseudo-damage ratio are smaller than LSM’s results, while test mileage and period of established specification exhibit significant improvement. These outcomes illustrate that it can more effectively develop durability test specification on vehicle proving ground that more realistically replicate the effects of fatigue damage to structures under actual user driving conditions.