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

Zhiqing Yu, Li Yang, Jianhui Zhao () and Leonid Grekhov
Additional contact information
Zhiqing Yu: School of Power and Energy Engineering, Harbin Engineering University, Harbin 150001, China
Li Yang: China Shipbuilding Power Engineering Institute, Co., Ltd., Shanghai 200120, China
Jianhui Zhao: School of Power and Energy Engineering, Harbin Engineering University, Harbin 150001, China
Leonid Grekhov: College of Power Engineering, Bauman Moscow State Technical University, Moscow 115569, Russia

Energies, 2024, vol. 17, issue 2, 1-18

Abstract: Under high-frequency operating conditions, the high-speed solenoid valve (HSV) experiences energy loss and heat generation, which significantly impacts its operational lifetime. Reducing the energy loss of an HSV without compromising its opening response characteristics poses a significant challenge. To address this issue, a finite element simulation model of an HSV coupled with a current feedback model is constructed to investigate the synergistic effects of dynamic response and energy loss. Prediction models for the opening response time, HSV driving energy, and Joule energy using a back propagation neural network (BPNN) are established. Furthermore, a multi-objective optimization study on the current driving strategy using a 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 an HSV driving strategy holds great significance for improving its working durability.

Keywords: high speed solenoid valve; dynamic response; energy loss; BPNN; NSGA-II; multi-objective optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/17/2/300/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/2/300/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:17:y:2024:i:2:p:300-:d:1314701

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().