A Comparative Study on Battery Modelling via Specific Hybrid Pulse Power Characterization Testing for Unmanned Aerial Vehicles in Real Flight Conditions
Battery modelling is essential for optimizing the performance and reliability of Unmanned Aerial Vehicles (UAVs), particularly given the challenges posed by their dynamic power demands and limited onboard computational resources. This study evaluates two widely adopted Equivalent Circuit Models (ECM...
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MDPI AG
2025-01-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/16/2/55 |
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| author | Waiard Saikong Prasophchok Phumma Suradet Tantrairatn Chaiyut Sumpavakup |
| author_facet | Waiard Saikong Prasophchok Phumma Suradet Tantrairatn Chaiyut Sumpavakup |
| author_sort | Waiard Saikong |
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| description | Battery modelling is essential for optimizing the performance and reliability of Unmanned Aerial Vehicles (UAVs), particularly given the challenges posed by their dynamic power demands and limited onboard computational resources. This study evaluates two widely adopted Equivalent Circuit Models (ECMs), the fixed resistance model and the Thevenin model to determine their suitability for UAV applications. Using the Specific Hybrid Pulse Power Characterization (SHPPC) method, key parameters, including Open Circuit Voltage (OCV), internal resistance (Ri), polarization resistance (R1), and polarization capacitance (C1), were estimated across multiple states of charge (SOC). The models were analyzed under nine parameterization scenarios, ranging from fully average parameters to configurations where selected parameters were tied to SOC. Results indicate that the Thevenin model, with selective SOC-dependent parameters, demonstrated superior predictive accuracy, achieving error reductions of up to 4.26 times compared to the fixed resistance model. Additionally, findings reveal that modelling all parameters as SOC-dependent is unnecessary, as simpler configurations can balance accuracy and computational efficiency, particularly for UAVs with constrained BMS capabilities. |
| format | Article |
| id | doaj-art-a226bba2dd724afba01aea37ce6c26b2 |
| institution | OA Journals |
| issn | 2032-6653 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj-art-a226bba2dd724afba01aea37ce6c26b22025-08-20T02:04:07ZengMDPI AGWorld Electric Vehicle Journal2032-66532025-01-011625510.3390/wevj16020055A Comparative Study on Battery Modelling via Specific Hybrid Pulse Power Characterization Testing for Unmanned Aerial Vehicles in Real Flight ConditionsWaiard Saikong0Prasophchok Phumma1Suradet Tantrairatn2Chaiyut Sumpavakup3Research Centre for Combustion Technology and Alternative Energy—CTAE, College of Industrial Technology, King Mongkut’s University of Technology North Bangkok, Bangkok 10800, ThailandDepartment of Power Engineering Technology, College of Industrial Technology, King Mongkut’s University of Technology North Bangkok, Bangkok 10800, ThailandSchool of Mechanical Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, ThailandResearch Centre for Combustion Technology and Alternative Energy—CTAE, College of Industrial Technology, King Mongkut’s University of Technology North Bangkok, Bangkok 10800, ThailandBattery modelling is essential for optimizing the performance and reliability of Unmanned Aerial Vehicles (UAVs), particularly given the challenges posed by their dynamic power demands and limited onboard computational resources. This study evaluates two widely adopted Equivalent Circuit Models (ECMs), the fixed resistance model and the Thevenin model to determine their suitability for UAV applications. Using the Specific Hybrid Pulse Power Characterization (SHPPC) method, key parameters, including Open Circuit Voltage (OCV), internal resistance (Ri), polarization resistance (R1), and polarization capacitance (C1), were estimated across multiple states of charge (SOC). The models were analyzed under nine parameterization scenarios, ranging from fully average parameters to configurations where selected parameters were tied to SOC. Results indicate that the Thevenin model, with selective SOC-dependent parameters, demonstrated superior predictive accuracy, achieving error reductions of up to 4.26 times compared to the fixed resistance model. Additionally, findings reveal that modelling all parameters as SOC-dependent is unnecessary, as simpler configurations can balance accuracy and computational efficiency, particularly for UAVs with constrained BMS capabilities.https://www.mdpi.com/2032-6653/16/2/55UAVbattery parameter estimationSHPPCEquivalent Circuit Modelreal flight data |
| spellingShingle | Waiard Saikong Prasophchok Phumma Suradet Tantrairatn Chaiyut Sumpavakup A Comparative Study on Battery Modelling via Specific Hybrid Pulse Power Characterization Testing for Unmanned Aerial Vehicles in Real Flight Conditions World Electric Vehicle Journal UAV battery parameter estimation SHPPC Equivalent Circuit Model real flight data |
| title | A Comparative Study on Battery Modelling via Specific Hybrid Pulse Power Characterization Testing for Unmanned Aerial Vehicles in Real Flight Conditions |
| title_full | A Comparative Study on Battery Modelling via Specific Hybrid Pulse Power Characterization Testing for Unmanned Aerial Vehicles in Real Flight Conditions |
| title_fullStr | A Comparative Study on Battery Modelling via Specific Hybrid Pulse Power Characterization Testing for Unmanned Aerial Vehicles in Real Flight Conditions |
| title_full_unstemmed | A Comparative Study on Battery Modelling via Specific Hybrid Pulse Power Characterization Testing for Unmanned Aerial Vehicles in Real Flight Conditions |
| title_short | A Comparative Study on Battery Modelling via Specific Hybrid Pulse Power Characterization Testing for Unmanned Aerial Vehicles in Real Flight Conditions |
| title_sort | comparative study on battery modelling via specific hybrid pulse power characterization testing for unmanned aerial vehicles in real flight conditions |
| topic | UAV battery parameter estimation SHPPC Equivalent Circuit Model real flight data |
| url | https://www.mdpi.com/2032-6653/16/2/55 |
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