Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Research on Multi-Objective Optimization of High-Speed Solenoid Valve Drive Strategies under the Synergistic Effect of Dynamic Response and Energy Loss

Version 1 : Received: 28 November 2023 / Approved: 28 November 2023 / Online: 29 November 2023 (07:31:11 CET)

A peer-reviewed article of this Preprint also exists.

Yu, Z.; Yang, L.; Zhao, J.; Grekhov, L. Research on Multi-Objective Optimization of High-Speed Solenoid Valve Drive Strategies under the Synergistic Effect of Dynamic Response and Energy Loss. Energies 2024, 17, 300. Yu, Z.; Yang, L.; Zhao, J.; Grekhov, L. Research on Multi-Objective Optimization of High-Speed Solenoid Valve Drive Strategies under the Synergistic Effect of Dynamic Response and Energy Loss. Energies 2024, 17, 300.

Abstract

Under high-frequency operating conditions, the high-speed solenoid valve (HSV) experiences energy loss and heat generation, which significantly impact its operational lifetime. Reducing the energy loss of HSV without compromising its opening response characteristics poses a significant challenge. To address this issue, a finite element simulation model of HSV coupled with a current feedback model is constructed to investigate the synergistic effects of dynamic response and energy loss. Predictive models for the opening response time, HSV driving energy, and Joule energy using Back Propagation neural network (BPNN) are established. Furthermore, a multi-objective optimization study on the current driving strategy using Non-dominated Sorting Genetic Algorithm II (NSGA-II) is conducted. After optimization, although there was a 6.24% increase in the opening response time, both HSV drive energy and Joule energy were significantly reduced by 15.67% and 22.49%, respectively. The proposed multi-objective optimization method for HSV driving strategy holds great significance in improving its working durability.

Keywords

High Speed solenoid valve; Dynamic response; Energy loss; BPNN; NSGA-II; multi-objective optimization

Subject

Engineering, Energy and Fuel Technology

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