Design of a hybrid State of Charge estimation algorithm for a Lithium Iron Phosphate low-voltage WRC Rally1 battery
This thesis explores the development and validation of an advanced Hybrid State of Charge estimation technique for a low-voltage Lithium Iron Phosphate battery, crucial for enhancing the battery management system of the World Rally Championship Rally1 car. The study reviews current battery technolog...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/428238 |
| Acceso en línea: | https://hdl.handle.net/2117/428238 |
| Access Level: | acceso abierto |
| Palabra clave: | Energy storage Lithium ion batteries Battery technology, Motorsport, Optimization, Simulation, Modeling, Electric Energia--Emmagatzematge Bateries d'ió liti Àrees temàtiques de la UPC::Energies |
| Sumario: | This thesis explores the development and validation of an advanced Hybrid State of Charge estimation technique for a low-voltage Lithium Iron Phosphate battery, crucial for enhancing the battery management system of the World Rally Championship Rally1 car. The study reviews current battery technology and common State of Charge techniques to develop hybrid method including Open Circuit Voltage identification with Coulomb counting, using a three-dimensional lookup table that correlates OCV, SOC, and temper- ature. This method aims to address the challenges posed by temperature variations and dynamic load profiles in accurately estimating SOC. The study uses data obtained from various standardized driving cycles, including DST, FUDS, and US06. By incorporating a moving window approach for OCV identification, the study optimizes the window length to minimize the Root Mean Square Error, and uses the Mean Absolute Error as a robust performance indicator for benchmark. The research highlights the impact of window size on the precision of SOC estimation while results demonstrate significant improvements in SOC estimation across different temperatures, with the proposed method effectively accounting for temperature-induced variations in the battery. This work contributes to the development of battery management systems and presents a innovative solution to State of Charge estimation based on already proven techniques. |
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