Relaxation Parameter Optimization in Electrical-to-Mechanical Co-Simulation Based on Time Windowing WR Technique
This paper presents an innovative approach to enhancing the time windowing waveform relaxation (WR) technique in electrical-to-mechanical co-simulation by optimizing relaxation parameters for improved performance. An analytical model is introduced to determine the optimal number of time windows, con...
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2025-01-01
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| author | Md Moktarul Alam Richard Perdriau Mohammed Ramdani Mohsen Koohestani |
| author_facet | Md Moktarul Alam Richard Perdriau Mohammed Ramdani Mohsen Koohestani |
| author_sort | Md Moktarul Alam |
| collection | DOAJ |
| description | This paper presents an innovative approach to enhancing the time windowing waveform relaxation (WR) technique in electrical-to-mechanical co-simulation by optimizing relaxation parameters for improved performance. An analytical model is introduced to determine the optimal number of time windows, considering the circuit’s dynamic characteristics. Additionally, a genetic algorithm (GA) is applied to refine relaxation parameters (e.g., impedance values), effectively addressing challenges posed by nonlinear device behaviors and improving the accuracy of co-simulation results. In the case study, it is crucial to emphasize that the full system simulation is used exclusively for retrospective validation of the co-simulation, without incorporating its results as inputs or convergence criteria. The proposed method significantly reduces the average error between co-simulation results and the full system output voltage, decreasing it from -2.8 dB to less than −26.2 dB. This demonstrates improved alignment and faster convergence compared to using the WR method. The validation of GA method is then applied to the co-simulation of an electrical (buck converter) and mechanical (DC motor) system, with results compared against the full system. The WR method exhibited significantly lower power efficiency (57.4%) compared to the full system (81.4%), rendering it insufficient. Time windowing WR enhanced power efficiency through simulation segmentation, reaching 74.6%, though it still fell short of the full system. The most advanced approach, time windowing WR with GA optimization, dynamically adjusted relaxation parameters, resulting in a power efficiency of 80.8%, nearly matching the 81.4% recorded in the single-kernel simulation. These findings underscore the effectiveness of integrating time segmentation with adaptive optimization to enhance simulation performance. |
| format | Article |
| id | doaj-art-bf2ee6cee9124e8583c386c5bda451cd |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| spelling | doaj-art-bf2ee6cee9124e8583c386c5bda451cd2025-08-20T01:49:51ZengIEEEIEEE Access2169-35362025-01-0113807758078510.1109/ACCESS.2025.356775210990266Relaxation Parameter Optimization in Electrical-to-Mechanical Co-Simulation Based on Time Windowing WR TechniqueMd Moktarul Alam0https://orcid.org/0000-0001-7186-9625Richard Perdriau1https://orcid.org/0000-0003-2494-6813Mohammed Ramdani2https://orcid.org/0000-0002-2398-1177Mohsen Koohestani3https://orcid.org/0000-0003-2194-3799École Supérieure d’Électronique de l’Ouest (ESEO), Angers, FranceÉcole Supérieure d’Électronique de l’Ouest (ESEO), Angers, FranceÉcole Supérieure d’Électronique de l’Ouest (ESEO), Angers, FranceÉcole Supérieure d’Électronique de l’Ouest (ESEO), Angers, FranceThis paper presents an innovative approach to enhancing the time windowing waveform relaxation (WR) technique in electrical-to-mechanical co-simulation by optimizing relaxation parameters for improved performance. An analytical model is introduced to determine the optimal number of time windows, considering the circuit’s dynamic characteristics. Additionally, a genetic algorithm (GA) is applied to refine relaxation parameters (e.g., impedance values), effectively addressing challenges posed by nonlinear device behaviors and improving the accuracy of co-simulation results. In the case study, it is crucial to emphasize that the full system simulation is used exclusively for retrospective validation of the co-simulation, without incorporating its results as inputs or convergence criteria. The proposed method significantly reduces the average error between co-simulation results and the full system output voltage, decreasing it from -2.8 dB to less than −26.2 dB. This demonstrates improved alignment and faster convergence compared to using the WR method. The validation of GA method is then applied to the co-simulation of an electrical (buck converter) and mechanical (DC motor) system, with results compared against the full system. The WR method exhibited significantly lower power efficiency (57.4%) compared to the full system (81.4%), rendering it insufficient. Time windowing WR enhanced power efficiency through simulation segmentation, reaching 74.6%, though it still fell short of the full system. The most advanced approach, time windowing WR with GA optimization, dynamically adjusted relaxation parameters, resulting in a power efficiency of 80.8%, nearly matching the 81.4% recorded in the single-kernel simulation. These findings underscore the effectiveness of integrating time segmentation with adaptive optimization to enhance simulation performance.https://ieeexplore.ieee.org/document/10990266/Co-simulationgenetic algorithmparameter optimizationtime windowing techniquewaveform relaxation |
| spellingShingle | Md Moktarul Alam Richard Perdriau Mohammed Ramdani Mohsen Koohestani Relaxation Parameter Optimization in Electrical-to-Mechanical Co-Simulation Based on Time Windowing WR Technique IEEE Access Co-simulation genetic algorithm parameter optimization time windowing technique waveform relaxation |
| title | Relaxation Parameter Optimization in Electrical-to-Mechanical Co-Simulation Based on Time Windowing WR Technique |
| title_full | Relaxation Parameter Optimization in Electrical-to-Mechanical Co-Simulation Based on Time Windowing WR Technique |
| title_fullStr | Relaxation Parameter Optimization in Electrical-to-Mechanical Co-Simulation Based on Time Windowing WR Technique |
| title_full_unstemmed | Relaxation Parameter Optimization in Electrical-to-Mechanical Co-Simulation Based on Time Windowing WR Technique |
| title_short | Relaxation Parameter Optimization in Electrical-to-Mechanical Co-Simulation Based on Time Windowing WR Technique |
| title_sort | relaxation parameter optimization in electrical to mechanical co simulation based on time windowing wr technique |
| topic | Co-simulation genetic algorithm parameter optimization time windowing technique waveform relaxation |
| url | https://ieeexplore.ieee.org/document/10990266/ |
| work_keys_str_mv | AT mdmoktarulalam relaxationparameteroptimizationinelectricaltomechanicalcosimulationbasedontimewindowingwrtechnique AT richardperdriau relaxationparameteroptimizationinelectricaltomechanicalcosimulationbasedontimewindowingwrtechnique AT mohammedramdani relaxationparameteroptimizationinelectricaltomechanicalcosimulationbasedontimewindowingwrtechnique AT mohsenkoohestani relaxationparameteroptimizationinelectricaltomechanicalcosimulationbasedontimewindowingwrtechnique |