Combined Sizing and Energy Management in EVs With Batteries and Supercapacitors
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Summary
This paper addresses the coupled problem of sizing and energy management for electric vehicles (EVs) equipped with hybrid energy storage systems (HESS) comprising batteries and supercapacitors (SCs). The primary motivation is to overcome the limitations of single-source storage, where batteries offer high energy density but limited power capability and cycle life, while SCs provide high power and durability but low energy density. The authors aim to determine the optimal number of battery and SC cells that minimizes installation and running costs while satisfying vehicle performance requirements, such as range, speed, and acceleration. The study highlights that sizing and energy management are interdependent; thus, optimizing them jointly is necessary to maximize hybridization benefits. The methodology employs two distinct approaches applied to a small EV (the uCar) using a deterministic driving cycle (ARTEMIS). The first approach utilizes a filter-based energy management strategy, where SCs handle high-frequency power peaks and batteries supply low-frequency steady-state power. Under practical assumptions, this sizing problem is formulated as a linear programming problem. The second approach employs an optimal, noncausal energy management strategy integrated with the sizing task, resulting in a nonlinear optimization problem. Both methods incorporate detailed models of the energy sources (using simplified voltage-resistor models for NiMH batteries and BCAP1500 SCs) and powertrain losses, including those from dc/dc converters, electric motors, and transmissions. The vehicle’s mass, including the HESS, is accounted for in the power and energy demand calculations. The results indicate that the filter-based approach, while simple and numerically efficient, generally requires an oversized storage unit compared to the optimal method. The optimal methodology outperforms the frequency-based approach by better exploiting the complementary features of the sources. Specifically, for EVs with modest range requirements (below 50 km in the case study), the inclusion of SCs enables energy savings of up to 7.8%. The study demonstrates that ignoring the coupling between sizing and energy management leads to suboptimal designs. Furthermore, the detailed loss modeling reveals that powertrain efficiency significantly impacts the optimal sizing, validating the need for comprehensive models in the design phase. The significance of this work lies in providing a rigorous framework for the co-design of HESS sizing and energy management. It establishes that joint optimization is critical for minimizing costs and maximizing efficiency in hybrid EVs. The findings suggest that for short-range applications, SCs offer substantial energy savings, justifying their inclusion despite higher initial costs. The paper contributes to the field by extending previous studies on fuel cell and hybrid EV sizing to battery-SC systems, offering practical insights for designers aiming to balance installation costs, energy efficiency, and battery degradation.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | OpenAlex-citations | — | — | 1 | 2026-06-19 |
| archive | success | semantic_scholar | — | — | 6 | 2026-06-25 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-19 |
| chunk | success | chunk | — | — | 1 | 2026-06-19 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-19 |
| promote | success | — | — | — | 1 | 2026-06-19 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-19 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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