Multi-objective optimization of an electrical injector in Urea-SCR system

Electrical injector is mainly used in non-air-assisted urea dosing systems to atomize and inject urea water solution. It consists of solenoid switch valve and injector. A good performance of the electrical injector can improve dosing precision of urea dosing system. To investigate dynamic characteristics of the electrical injector, an equivalent magnetic circuit model of the solenoid valve was established and magnetic field of the solenoid valve was also simulated using a three-dimensional finite element model. The results show that the calculation error of the two models is 6%, demonstrating that the equivalent magnetic circuit model can effectively predict the magnetic characteristics of the solenoid. Taking opening time, closing time, and coil area of the electrical injector as objective functions, a multi-objective optimization algorithm was used to optimize the design parameters of the electrical injector. Opening and closing processes of the optimized electrical injector under different pressures and driving voltages were measured through laser triangulation sensor. The experimental results showed that calculation results of the proposed theoretical model were close to the measurement results. The opening time of the optimized injector has been reduced by 11%, the response of the injector has significantly improved.

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Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
Published
2024-12-10
DOI
https://doi.org/10.1177/09544070241301663
Citations
1
Primary Topic
Electrohydrodynamics and Fluid Dynamics
Type
article
Field-Weighted Citation Impact
0.21

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article

Multi-objective optimization of an electrical injector in Urea-SCR system

Youcheng Shi, Junfeng Shan, Zheng Li, Hucheng Zhang
1 citations
Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering
Electrohydrodynamics and Fluid Dynamics
0.21
article

Multi-objective optimization of an electrical injector in Urea-SCR system

Youcheng Shi, Junfeng Shan, Zheng Li, Hucheng Zhang
article en
1 citations

Abstract

Electrical injector is mainly used in non-air-assisted urea dosing systems to atomize and inject urea water solution. It consists of solenoid switch valve and injector. A good performance of the electrical injector can improve dosing precision of urea dosing system. To investigate dynamic characteristics of the electrical injector, an equivalent magnetic circuit model of the solenoid valve was established and magnetic field of the solenoid valve was also simulated using a three-dimensional finite element model. The results show that the calculation error of the two models is 6%, demonstrating that the equivalent magnetic circuit model can effectively predict the magnetic characteristics of the solenoid. Taking opening time, closing time, and coil area of the electrical injector as objective functions, a multi-objective optimization algorithm was used to optimize the design parameters of the electrical injector. Opening and closing processes of the optimized electrical injector under different pressures and driving voltages were measured through laser triangulation sensor. The experimental results showed that calculation results of the proposed theoretical model were close to the measurement results. The opening time of the optimized injector has been reduced by 11%, the response of the injector has significantly improved.

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile EngineeringVol. 239(13)
Lanzhou University of Technology (CN)
Natural Science Foundation of Gansu Province, National Key Research and Development Program of China
Clean water and sanitation
Openalex Percentile: Top 45%
Electrohydrodynamics and Fluid Dynamics
0.21
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Multi-objective optimization of an electrical injector in Urea-SCR system — Youcheng Shi, Junfeng Shan, et al. · Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering (2024) | TGRS Research Map | TGRS