Hybrid Reliability Approach for Airbag Protection Performance Based on Probability and Ellipsoidal Convex Models

doi:10.3901/JME.2020.02.130

Abstract

Abstract: Considering the influence of multi-source uncertainties on airbag protection performance, a hybrid reliability approach based on probability and ellipsoidal convex models is presented for airbag protection performance. Firstly, the probability and ellipsoidal convex models are used to quantify the uncertainty,and the reliability analysis model of airbag protection performance will be constructed. Then, considering the original hybrid reliability analysis belongs to a complex nesting optimization problem, an efficient decoupling strategy is suggested to improve the computational efficiency. Based on this decoupling strategy, the normalized hybrid reliability model can be converted into the singer-layer equivalent model by utilizing the Karush-Kuhn-Tucker conditions. Finally, the intergeneration projection genetic algorithm (IP-GA) is adopted to obtained the reliability index of airbag protection performance, which is validated by the vehicle airdrop experiments. The results demonstrate that the proposed method could effectively evaluate the reliability of airbag protection performance and ensure the vehicle safety. The method can also be used in the field of other airdrop protections.

Key words: airbag, equipment airdrop, correlation, hybrid model, reliability analysis

CLC Number:

V224

LIU Xin, YIN Lairong, HU Lin. Hybrid Reliability Approach for Airbag Protection Performance Based on Probability and Ellipsoidal Convex Models[J]. Journal of Mechanical Engineering, 2020, 56(2): 130-137.

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