Optimization of CNG Direct Injector Parameters using model-based calibration framework
This paper presents an optimization study conducted based on a direct injector model running on compressed natural gas. The purpose of the study is to identify the optimal setup for the selected input parameters which deliver maximum injection quantity at the lowest solenoid current. The optimized i...
| Main Authors: | , , |
|---|---|
| Format: | Book Chapter |
| Language: | English |
| Published: |
Springer
2021
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/32025/ http://umpir.ump.edu.my/id/eprint/32025/1/OPTIMIZATION%20OF%20CNG%20DIRECT%20INJECTOR%20USING%20MODEL%20BASED%20CALIBRATION%20V.2.pdf |
| _version_ | 1848823918670905344 |
|---|---|
| author | Mohamad Hafidzul Rahman, Alias Mohd Fadzil, Abdul Rahim Rosli, Abu Bakar |
| author_facet | Mohamad Hafidzul Rahman, Alias Mohd Fadzil, Abdul Rahim Rosli, Abu Bakar |
| author_sort | Mohamad Hafidzul Rahman, Alias |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | This paper presents an optimization study conducted based on a direct injector model running on compressed natural gas. The purpose of the study is to identify the optimal setup for the selected input parameters which deliver maximum injection quantity at the lowest solenoid current. The optimized injector input parameters were the injection pressure, injection duration, and input voltage. The optimization study was conducted using MATLAB’s Simulink, Model-Based Calibration (MBC) Toolbox and injector test rig. The optimization data is generated by a validated, zero-dimensional, first principle injector model. The optimize calibration results were implemented in the injector experiment for verification. It was found that the simulation result of the mass flow rate for baseline versus optimization shows an increment of 15.64%. In comparison, the experimental result for baseline versus optimization shows an increase of 35.79%. Additionally, a comparison between the baseline work for simulation versus experiment produced RMSE of 0.2467 while the optimization work for simulation versus the experiment provides an RMSE value of 0.1860. |
| first_indexed | 2025-11-15T03:04:46Z |
| format | Book Chapter |
| id | ump-32025 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:04:46Z |
| publishDate | 2021 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-320252021-09-14T06:59:35Z http://umpir.ump.edu.my/id/eprint/32025/ Optimization of CNG Direct Injector Parameters using model-based calibration framework Mohamad Hafidzul Rahman, Alias Mohd Fadzil, Abdul Rahim Rosli, Abu Bakar TK Electrical engineering. Electronics Nuclear engineering This paper presents an optimization study conducted based on a direct injector model running on compressed natural gas. The purpose of the study is to identify the optimal setup for the selected input parameters which deliver maximum injection quantity at the lowest solenoid current. The optimized injector input parameters were the injection pressure, injection duration, and input voltage. The optimization study was conducted using MATLAB’s Simulink, Model-Based Calibration (MBC) Toolbox and injector test rig. The optimization data is generated by a validated, zero-dimensional, first principle injector model. The optimize calibration results were implemented in the injector experiment for verification. It was found that the simulation result of the mass flow rate for baseline versus optimization shows an increment of 15.64%. In comparison, the experimental result for baseline versus optimization shows an increase of 35.79%. Additionally, a comparison between the baseline work for simulation versus experiment produced RMSE of 0.2467 while the optimization work for simulation versus the experiment provides an RMSE value of 0.1860. Springer 2021-07-16 Book Chapter PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/32025/1/OPTIMIZATION%20OF%20CNG%20DIRECT%20INJECTOR%20USING%20MODEL%20BASED%20CALIBRATION%20V.2.pdf Mohamad Hafidzul Rahman, Alias and Mohd Fadzil, Abdul Rahim and Rosli, Abu Bakar (2021) Optimization of CNG Direct Injector Parameters using model-based calibration framework. In: Recent Trends in Mechatronics Towards Industry 4.0. Lecture Notes in Electrical Engineering, 730 (1). Springer, Singapore, pp. 917-929. ISBN 978-981-33-4596-6 (Print) 978-981-33-4597-3 (Online) https://doi.org/10.1007/978-981-33-4597-3_83 DOI https://doi.org/10.1007/978-981-33-4597-3_83 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Mohamad Hafidzul Rahman, Alias Mohd Fadzil, Abdul Rahim Rosli, Abu Bakar Optimization of CNG Direct Injector Parameters using model-based calibration framework |
| title | Optimization of CNG Direct Injector Parameters using model-based calibration framework |
| title_full | Optimization of CNG Direct Injector Parameters using model-based calibration framework |
| title_fullStr | Optimization of CNG Direct Injector Parameters using model-based calibration framework |
| title_full_unstemmed | Optimization of CNG Direct Injector Parameters using model-based calibration framework |
| title_short | Optimization of CNG Direct Injector Parameters using model-based calibration framework |
| title_sort | optimization of cng direct injector parameters using model-based calibration framework |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/32025/ http://umpir.ump.edu.my/id/eprint/32025/ http://umpir.ump.edu.my/id/eprint/32025/ http://umpir.ump.edu.my/id/eprint/32025/1/OPTIMIZATION%20OF%20CNG%20DIRECT%20INJECTOR%20USING%20MODEL%20BASED%20CALIBRATION%20V.2.pdf |