Optimized Solution Method for Vehicle Durability User-correlated Model Based on Signal Weight Analysis
The test specification rationality of the test site directly affects the credibility of vehicle durability testing results.To address the issue of neglecting the priority level of correlated channels when solving the damage-correlated model of the'user-test site',an optimization method based on weight analysis of the correlated channels was proposed.A series of sub-objectives were divided according to vehicle correlation requirements and signal types.The weights of the sub-objective functions were analyzed using the criteria importance through intercriteria correlation(CRITIC)approach,and a new comprehensive objective function was constructed by merging the weights using the compromise programming method.Finally,the function was solved using the genetic algorithm.Correlation analysis validation was conducted on a light commercial vehicle to evaluate the effectiveness of the methodologies proposed.Five sub-objects of the vehicle were defined,including wheel center vertical force,longitudinal/lateral force,suspension displacement,force,and strain signals.These sub-objects were assigned weights of 0.255,0.230,0.153,0.203,and 0.159,respectively.Then,the comprehensive objective function was established and subsequently solved to obtain the cycles of the reinforced testing roads.The obtained solution was compared with that from the direct multi-objective solution method.The results indicate that the relative damage ratios of the key channels-wheel center vertical forces match 0.8-1.1,and the rest maintain between 0.5-2,while the relative damage ratios calculated via the direct multi-objective-based method range between 0.4-2.5.This suggests that the proposed method effectively reflects the importance of each correlated sub-target and achieves a more consistent reproduction of vehicle damage under correlation-matching requirements in practical applications.Moreover,the corresponding load distribution and test mileage show that the developed test specification meets the theoretical demands of an enhanced acceleration test in actual engineering.This research provides a valuable reference for vehicle durability testing.
automotive engineeringuser-correlated model optimizationobjective weighting coef-ficientdurability test specificationcomprehensive objective functiongenetic algorithm
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