Multi-Parameter-Based State of Health Observation Method for Second-Hand Hybrid Electric Vehicle Batteries Operating in Extreme Climates
The global shift toward electrified transportation is accelerating as nations work to reduce carbon emissions and combat climate change. Second-hand hybrid electric vehicles (HEVs) have become a practical alternative in developing countries like Mongolia due to their affordability and fuel efficienc...
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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/11053752/ |
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Summary: | The global shift toward electrified transportation is accelerating as nations work to reduce carbon emissions and combat climate change. Second-hand hybrid electric vehicles (HEVs) have become a practical alternative in developing countries like Mongolia due to their affordability and fuel efficiency. However, the degradation of nickel-metal hydride (NiMH) batteries in aging HEVs presents a significant challenge, particularly in Mongolia’s extreme climate conditions, which accelerate battery deterioration. Existing state of health (SOH) estimation methods often face limitations in accuracy, consistency, and practicality, reducing their effectiveness in real-world applications. This paper proposes a novel SOH observation method tailored for second-hand HEVs operating in harsh environmental conditions to address these challenges. The proposed method utilizes multiple battery parameters, including current, voltage, temperature, internal resistance, and capacity, to improve estimation accuracy while maintaining simplicity and efficiency. The effectiveness of the proposed method is validated through simulation and experimental analysis, demonstrating a correlation between predicted and actual battery health. The findings offer a reliable and practical solution for battery health monitoring, enhancing vehicle performance, informing consumer decisions, and supporting the sustainable adoption of HEVs. |
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ISSN: | 2169-3536 |