Modeling and impact assessment of hybrid battery–supercapacitor energy storage solutions for electric vehicles
This paper presents a comprehensive modeling and control framework for electric vehicles (EVs) equipped with a hybrid energy storage system combining a battery and a supercapacitor. The proposed approach includes detailed representations of road loads, thermal and electrical behavior of power train...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2026 |
| 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:2117/454228 |
| Acceso en línea: | https://hdl.handle.net/2117/454228 https://dx.doi.org/10.1016/j.est.2026.120811 |
| Access Level: | acceso embargado |
| Palabra clave: | Hybrid energy storage Battery Battery management system Supercapacitor Electric vehicle Electric motor Regenerative braking Àrees temàtiques de la UPC::Enginyeria elèctrica |
| Sumario: | This paper presents a comprehensive modeling and control framework for electric vehicles (EVs) equipped with a hybrid energy storage system combining a battery and a supercapacitor. The proposed approach includes detailed representations of road loads, thermal and electrical behavior of power train components, and advanced control strategies for motor speed and torque regulation, as well as for the active management of the supercapacitor and battery packs. These controllers, based on PI structures and enhanced with Maximum Torque Per Ampere (MTPA) and field weakening techniques for the motor, are complemented by Safe Operating Area (SOA)-based constraints to ensure safe operation of the battery and supercapacitor under varying State of Charge (SoC) conditions. In addition, the power control of the supercapacitor pack, since being the cornerstone of the performance of the active hybrid topology proposed in the paper, is tested under two control strategies, both tuned using H- control theory to guarantee robustness and dynamic performance. Simulation results demonstrate that active hybridization significantly outperforms passive configurations and the base case (no hybrid solution) in terms of battery power stress reduction and regenerative braking efficiency. Notably, battery peak discharge power can be reduced by up to 53.2%, and power cycling frequency and severity is mitigated. Regenerative braking is enhanced by shifting charge demand to the supercapacitor, although sizing trade-offs are observed: larger packs improve buffering but increase vehicle weight and energy consumption. These findings highlight the potential of actively controlled hybrid energy storage solutions to improve EV performance and durability. |
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