Thursday, August 07, 2025

 

A breakthrough in state-of-charge estimation for battery management of electric vehicles




Beijing Institute of Technology Press Co., Ltd
A strong robust state-of-charge estimation method based on the gas-liquid dynamics model 

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A strong robust state-of-charge estimation method based on the gas-liquid dynamics model

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Credit: GREEN ENERGY AND INTELLIGENT TRANSPORTATION





In the rapidly evolving landscape of electric vehicles (EVs) and large-scale energy storage systems, accurate battery management remains a critical challenge. The state-of-charge (SOC) estimation—essentially how much "fuel" is left in your battery—has long been a complex engineering problem due to the dynamic nature of battery behavior under various conditions. Traditional methods often struggle with initial errors, cumulative inaccuracies, and sparse data collection scenarios, limiting their real-world applicability. This groundbreaking research introduces a novel approach that combines the gas-liquid dynamics model (GLDM) with an advanced filtering algorithm to overcome these persistent challenges.

 

The researchers from Huaiyin Institute of Technology present remarkable improvements in battery SOC estimation across multiple dimensions:

(1) Exceptional Accuracy: The proposed method achieves a maximum SOC error of just 0.016 (1.6%) under normal conditions—a level of precision critical for reliable EV range estimation.

 

(2) Unparalleled Error Recovery: When faced with a significant initial error of 50%, the new method corrects itself within just 5 seconds, while conventional approaches require over 100 seconds—a 20-fold improvement in recovery speed.

 

(3) Resilience to Battery Aging: Even when battery capacity deteriorates to 60% of its original value (a common scenario in aging EVs), the maximum SOC estimation error remains below 0.025 (2.5%), ensuring reliable performance throughout the battery's lifecycle.

 

(4) Robust Performance with Sparse Data: Unlike traditional methods that rapidly lose accuracy when sampling frequency decreases, the proposed approach maintains a slow linear growth in error. At a sampling period of 24 seconds—far longer than typical systems—the Root Mean Square Error (RMSE) remains at approximately 0.01, demonstrating exceptional stability.

 

This technological breakthrough opens doors to numerous advancements in electric mobility and energy storage: (1) Extended EV Range Confidence: More accurate SOC estimation means drivers can trust their vehicle's range indicators, reducing "range anxiety" and encouraging broader EV adoption. (2) Optimized Fast-Charging Systems: The method's ability to accurately track battery states could enable more efficient fast-charging protocols that maximize charging speed while preserving battery health. (3) Smart Grid Integration: Large-scale battery storage systems using this technology could provide more reliable grid services, enhancing the integration of renewable energy sources. (4) Next-Generation Battery Management: Future research could extend this approach to different battery chemistries like LiFePO4 and multi-cell battery modules, potentially creating a universal battery management solution. (5) Resource-Efficient Implementation: The computational efficiency of this method makes it suitable for implementation in existing battery management systems without requiring hardware upgrades.

 

This innovative SOC estimation method represents a significant leap forward in battery management technology. By combining the gas-liquid dynamics model with an advanced dual extended Kalman filter featuring a watchdog function, the research addresses the fundamental challenges that have limited battery management systems for years. As electric vehicles and renewable energy storage continue their rapid growth, this technology promises to enhance reliability, extend usable battery life, and ultimately accelerate our transition to sustainable transportation and energy systems.

 

 

Reference

 

Author: Biao Chen a c, Liang Song b, Haobin Jiang c, Zhiguo Zhao a c, Jun Zhu a, Keqiang Xu a

 

Title of original paper: A strong robust state-of-charge estimation method based on the gas-liquid dynamics model

 

Article link: https://www.sciencedirect.com/science/article/pii/S2773153724000458

 

Journal: Green Energy and Intelligent Transportation

DOI: 10.1016/j.geits.2024.100193

Affiliations:

a Jiangsu Key Laboratory of Traffic and Transportation Security, Huaiyin Institute of Technology, Huai'an 223003, China

b Faculty of Chemical Engineering, Huaiyin Institute of Technology, Huai'an 223003, China

c Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China

Bridging the gap between solar intermittency and reliable power: Dual-level design extends battery life and optimizes costs




Beijing Institute of Technology Press Co., Ltd
Dual-level design for cost-effective sizing and power management of hybrid energy storage in photovoltaic systems 

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Dual-level design for cost-effective sizing and power management of hybrid energy storage in photovoltaic systems

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Credit: GREEN ENERGY AND INTELLIGENT TRANSPORTATION






In an era where renewable energy is rapidly transforming our power grids, solar photovoltaic (PV) systems face a persistent challenge: the sun doesn't always shine when we need electricity most. Researchers at Aalborg University have developed an innovative solution that could significantly advance how we store and manage solar energy, making renewable power more reliable and cost-effective.

 

The research team has created a dual-level design approach for hybrid energy storage systems (HESS) that combines lithium-ion batteries with supercapacitors in solar installations. This breakthrough addresses one of the most significant barriers to widespread solar adoption – the intermittent nature of sunlight and the resulting stress on batteries that store solar energy.

 

The study's results demonstrate remarkable improvements in system performance:

- Battery cycling reduced by up to 13% over a one-year period, significantly extending battery lifespan

- Maintained optimal self-sufficiency of the solar system while reducing operational costs

- Successfully managed power ramp-rate constraints, ensuring grid stability

- Balanced energy throughput between the PV system and the grid for maximum cost-effectiveness

 

"By intelligently combining lithium-ion batteries with supercapacitors, we're leveraging the strengths of each technology," explains the research team. "Supercapacitors handle the rapid power fluctuations that typically degrade batteries, while the batteries manage longer-term energy storage needs."

 

The system employs an innovative adaptive filter that dynamically distributes power between batteries and supercapacitors based on real-time conditions. This approach ensures that each component operates within its optimal parameters, extending the overall system life and reducing replacement costs.

 

The researchers are now looking to expand their work to include additional battery aging factors and validate their findings with real battery cells in field conditions. Future research will also quantify economic benefits more precisely, providing a comprehensive techno-economic analysis. This dual-level design represents a significant step forward in making solar energy more practical and economically viable. By addressing the fundamental challenges of energy storage in renewable systems, the research contributes to accelerating the global transition to clean energy.

 

As solar installations continue to grow worldwide, innovative approaches to energy storage like this will be crucial in building a more sustainable and resilient energy infrastructure. The combination of smart sizing methodology and adaptive power management demonstrates how thoughtful engineering can overcome the inherent challenges of renewable energy, bringing us closer to a future powered by the sun.

Reference

 

Author: Xiangqiang Wu, Zhongting Tang, Daniel-Ioan Stroe, Tamas Kerekes

 

Title of original paper: Dual-level design for cost-effective sizing and power management of hybrid energy storage in photovoltaic systems

 

Article link: https://www.sciencedirect.com/science/article/pii/S277315372400046X

 

Journal: Green Energy and Intelligent Transportation

 

DOI: 10.1016/j.geits.2024.100194

 

Affiliations:

Department of AAU Energy, Aalborg University, Aalborg 9220, Denmark

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