The reliability of electromagnetic relays is affected by dynamic and contact bounce behaviors. To address this issue, a novel optimal parameter design strategy based on a nonlinear contact model and constrained optimization method is proposed to compensate for the effects of complicated contact bounces. Dynamic response is considered within a multi-objective optimization problem, which balances closure efficiency and bounce optimization. Given engineering design requirements, a constrained multi-objective optimization model is built. To solve the optimization model and search Pareto solutions of optimal design parameters, a self-adaptive updating operator is included in the multi-objective differential evolution algorithm. Considering the robustness requirement and parameter uncertainties introduced by the manufacturing process, a robustness evaluation criterion based on Monte Carlo simulation is used to attain the most robust set of design parameters from the Pareto solutions. The feasibility and effectiveness of the proposed strategy are well verified by commercial electromagnetic relays, including specific achievements such as a computational accuracy of 96.34% for the nonlinear contact model, complete suppression of contact bounce in the optimized relay, and the identification of five sets of design parameters that meet the reliability requirements of electromagnetic relays while considering the robustness of these parameters. Graphical abstract: [Figure not available: see fulltext.]

A novel methodology for the optimization of design parameters of electromagnetic relays

Zio E.;
2024-01-01

Abstract

The reliability of electromagnetic relays is affected by dynamic and contact bounce behaviors. To address this issue, a novel optimal parameter design strategy based on a nonlinear contact model and constrained optimization method is proposed to compensate for the effects of complicated contact bounces. Dynamic response is considered within a multi-objective optimization problem, which balances closure efficiency and bounce optimization. Given engineering design requirements, a constrained multi-objective optimization model is built. To solve the optimization model and search Pareto solutions of optimal design parameters, a self-adaptive updating operator is included in the multi-objective differential evolution algorithm. Considering the robustness requirement and parameter uncertainties introduced by the manufacturing process, a robustness evaluation criterion based on Monte Carlo simulation is used to attain the most robust set of design parameters from the Pareto solutions. The feasibility and effectiveness of the proposed strategy are well verified by commercial electromagnetic relays, including specific achievements such as a computational accuracy of 96.34% for the nonlinear contact model, complete suppression of contact bounce in the optimized relay, and the identification of five sets of design parameters that meet the reliability requirements of electromagnetic relays while considering the robustness of these parameters. Graphical abstract: [Figure not available: see fulltext.]
2024
Constrained optimization
Contact bounce
Electromagnetic relay
Nonlinear dynamics
Parameter design
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1278014
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