EPE Association: EPE 2025 - LS6b: Energy Storage and Management Systems

EPE 2025 - LS6b: Energy Storage and Management Systems
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2025 - Conference > EPE 2025 - Topic 03: Energy Storage Systems > EPE 2025 - LS6b: Energy Storage and Management Systems

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   Impact of Model Depth on State of Charge Estimation in Second-Life Batteries
By Lukas BÖHNING, Mathias HERGET, Patrick STOCK, Sven FIESSER, Raphael KRESS, Ulf SCHWALBE [View]
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Abstract: This paper investigates the impact of different levels of modelling on the accuracy of state of charge estimation in battery storage systems. The aim is to compare simple and complex models to identify the optimal balance between accuracy and computational complexity. The results show that while deeper models improve estimation, the additional complexity provides only marginal benefits. A kinetic approach improves accuracy at high loads without significantly increasing the effort. Separating the inverter and battery models increases flexibility by allowing system changes without retooling. The results provide a basis for integrating temperature effects and optimising storage operation for economic efficiency.

   Improved estimation of battery equivalent resistance in bidirectional EV chargers
By Mohammad Sadegh BAGHAEI NANE KARAN, Zohra KADER, Maurice FADEL, Jerome LACHAIZE [View]
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Abstract: This paper presents an analysis and modelling approach for bidirectional CLLLC resonant converters, addressing limitations in conventional methods like the First Harmonic Approximation (FHA). The proposed methodology based on Extended Harmonic Analysis (EHA) allows a dynamical estimation of a battery equivalent resistance across varying frequency and voltage ranges. The precision of gain characterization and performance are improved using the proposed method. MATLAB Simulink simulations validate the proposed EHA method, demonstrating significant improvements in prediction accuracy and power transfer efficiency. Compared to FHA, the EHA method reduces modelling errors by up to 78\%.

   Modeling the steady state response of the solid phase diffusion process in Lithium-ion cells
By Ghada BAKARAKI, Houssam RABAB, Nicolas DAMAY, Khadija EL KADRI BENKARA, Christophe FORGEZ [View]
[Download]

Abstract: Accurate battery models are crucial for the evaluation of Lithium-ion batteries states and performance. Physics based models can represent the battery's non-linear behavior but may not take into account the whole battery's phenomena given the high complexity of the equations. Despite their simplicity, traditional equivalent circuit models (ECM) may not represent non-linear behaviour especially in low state of charge (SoC) area. To take the best of the above modeling approaches, a physics-based ECM is presented. This model is built on separating solid and liquid diffusion effects in Li-ion cells whose diffusion is strongly non-linear with SoC. A detailed identification methodology of the solid diffusion's steady-state response was proposed. Thanks to this model, diffusion parameters present less non-linearities and are easier to be identified, while reducing the dimensions of lookup tables and characterization tests time.

EPE 2025 - LS6b: Energy Storage and Management Systems
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2025 - Conference > EPE 2025 - Topic 03: Energy Storage Systems > EPE 2025 - LS6b: Energy Storage and Management Systems
	[return to parent folder]

	Impact of Model Depth on State of Charge Estimation in Second-Life Batteries By Lukas BÖHNING, Mathias HERGET, Patrick STOCK, Sven FIESSER, Raphael KRESS, Ulf SCHWALBE	[View] [Download]
Abstract: This paper investigates the impact of different levels of modelling on the accuracy of state of charge estimation in battery storage systems. The aim is to compare simple and complex models to identify the optimal balance between accuracy and computational complexity. The results show that while deeper models improve estimation, the additional complexity provides only marginal benefits. A kinetic approach improves accuracy at high loads without significantly increasing the effort. Separating the inverter and battery models increases flexibility by allowing system changes without retooling. The results provide a basis for integrating temperature effects and optimising storage operation for economic efficiency.

	Improved estimation of battery equivalent resistance in bidirectional EV chargers By Mohammad Sadegh BAGHAEI NANE KARAN, Zohra KADER, Maurice FADEL, Jerome LACHAIZE	[View] [Download]
Abstract: This paper presents an analysis and modelling approach for bidirectional CLLLC resonant converters, addressing limitations in conventional methods like the First Harmonic Approximation (FHA). The proposed methodology based on Extended Harmonic Analysis (EHA) allows a dynamical estimation of a battery equivalent resistance across varying frequency and voltage ranges. The precision of gain characterization and performance are improved using the proposed method. MATLAB Simulink simulations validate the proposed EHA method, demonstrating significant improvements in prediction accuracy and power transfer efficiency. Compared to FHA, the EHA method reduces modelling errors by up to 78\%.

	Modeling the steady state response of the solid phase diffusion process in Lithium-ion cells By Ghada BAKARAKI, Houssam RABAB, Nicolas DAMAY, Khadija EL KADRI BENKARA, Christophe FORGEZ	[View] [Download]
Abstract: Accurate battery models are crucial for the evaluation of Lithium-ion batteries states and performance. Physics based models can represent the battery's non-linear behavior but may not take into account the whole battery's phenomena given the high complexity of the equations. Despite their simplicity, traditional equivalent circuit models (ECM) may not represent non-linear behaviour especially in low state of charge (SoC) area. To take the best of the above modeling approaches, a physics-based ECM is presented. This model is built on separating solid and liquid diffusion effects in Li-ion cells whose diffusion is strongly non-linear with SoC. A detailed identification methodology of the solid diffusion's steady-state response was proposed. Thanks to this model, diffusion parameters present less non-linearities and are easier to be identified, while reducing the dimensions of lookup tables and characterization tests time.