EPE Association: EPE 2025 - DS2b: Battery Aging, Reliability, and Safety

EPE 2025 - DS2b: Battery Aging, Reliability, and Safety
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2025 - Conference > EPE 2025 - Topic 03: Energy Storage Systems > EPE 2025 - DS2b: Battery Aging, Reliability, and Safety

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   A comparison of lithium diffusion between Graphite/LFP 18650 power and energy cells with low and high current pulses
By William WHEELER, Damien VOYER [View]
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Abstract: This study gives a new estimation model to evaluate the voltage-increase due to a step-up current in both lithium-ion power and energy cells. The step-up current analysis is similar to the GITT technic developed in the literature, but with tests at low or high C-rate and for a longer time. The power cell voltage-increase follows a square root of time dependency which is commonly observed in the literature. On the contrary, a superimposed transient overvoltage in the energy cell is observed. The transient overvoltage has the capacity to distort the characterization of diffusion as modelled by existing models. This paper proposes a phenomenological approach to model the transient overvoltage in the energy cell. This work gives a method to model the phenomenon and is a first step to clarify the origin of the phenomenon. It can also help improving the estimation of the diffusion parameters.

   A high-performance AC excitation and measuring system for on-line estimation of Lithium-ion battery cells' internal impedance
By Ioannis BOTAS, Olga SOKOLAKI, Emmanuel TATAKIS [View]
[Download]

Abstract: Nowadays, there is a rapid increase in the use of Lithium-Ion batteries for many different applications, due to their superiority in terms of energy density, efficiency, and self-discharge rate. In this paper, a high-performance system for estimation of Lithium-ion battery cells' internal impedance is presented. The main concept lies in the excitation of cells through a multi-sine controlled current signal, instead of using the time-consuming sequential harmonic injection. The proposed technique was implemented for a LiFePO4, 3.2V/30Ah battery cell through a bi-directional power converter, for integrating both charging and discharging capability. A laboratory prototype of this converter was designed and implemented, to investigate theoretical assumptions. The experimental results are eventually analyzed, to evaluate the influence of the various experimental conditions on the cell internal impedance.

   Battery pack thermal management using phase change materials for small electric vehicles
By Mohammed MASHAQI, Nassim RIZOUG, Cherif LAROUCI, Mustapha KARKRI, Mahamadou Abdou TANKARI [View]
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Abstract: Lithium-ion batteries are crucial in automotive applications due to their high energy storage capacity. However, batteries require thermal management to mitigate the negative effects of low, high, and non-uniform temperatures. In this study, we propose a novel battery pack thermal management system based on phase change materials (PCMs) for use in small electric vehicles. PCMs are promising for thermal management systems because of their high thermal energy storage capacity at a constant temperature and their low cost. However, their low thermal conductivity poses a significant challenge. To address this issue, aluminum honeycomb panels are incorporated to the PCM as a PCM heat transfer enhancement technique. This research investigates the impact of using PCM as thermal management system and analyzes the evolution of battery temperature over time with and without PCM under various ambient temperatures. Additionally, the effect of adding an external insulation to the battery pack is examined. The results demonstrate that integrating PCMs between every two battery rows in the pack reduces the battery temperature by 9.8°C compared to the scenario without a thermal management system. Furthermore, At 40°C ambient temperature, adding external insulation reduces the battery temperature by 1.6°C with PCM and by 2.25°C without PCM, both compared to uninsulated cases. These materials shows its potential to serve as an alternative to some traditional cooling methods that rely on fans and pumps.

   Optimized Estimation of Battery ParametersCapacity, Resistances and SOC for ElectricVehicles: A Hybrid Approach Based onGenetic Algorithm and Artificial Intelligence
By Jamila HEMDANI, Laid DEGAA, Nassim RIZOUG, Moez SOLTANI, Achraf TELMOUDI, Abdelkader CHAARI [View]
[Download]

Abstract: Index Terms\_AI-Enhanced Battery Modeling forElectric Vehicles: Real-Time Parameter Optimization andState EstimationAbstract\_In this paper, we present a method foroptimizing the key parameters of an equivalent electricalmodel of a battery (Rohmic, R1, C1) and its capacity (Cbat)using advanced artificial intelligence techniques. The goalis to improve the accuracy of the estimation of the State ofCharge (SOC) and State of Health (SOH). We introducea dynamic optimization approach where resistances andcapacitances are adjusted at each time step, while Cbatis optimized over a full cycle. The results demonstrate asignificant improvement in terms of reducing predictionerrors.

EPE 2025 - DS2b: Battery Aging, Reliability, and Safety
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2025 - Conference > EPE 2025 - Topic 03: Energy Storage Systems > EPE 2025 - DS2b: Battery Aging, Reliability, and Safety
	[return to parent folder]

	A comparison of lithium diffusion between Graphite/LFP 18650 power and energy cells with low and high current pulses By William WHEELER, Damien VOYER	[View] [Download]
Abstract: This study gives a new estimation model to evaluate the voltage-increase due to a step-up current in both lithium-ion power and energy cells. The step-up current analysis is similar to the GITT technic developed in the literature, but with tests at low or high C-rate and for a longer time. The power cell voltage-increase follows a square root of time dependency which is commonly observed in the literature. On the contrary, a superimposed transient overvoltage in the energy cell is observed. The transient overvoltage has the capacity to distort the characterization of diffusion as modelled by existing models. This paper proposes a phenomenological approach to model the transient overvoltage in the energy cell. This work gives a method to model the phenomenon and is a first step to clarify the origin of the phenomenon. It can also help improving the estimation of the diffusion parameters.

	A high-performance AC excitation and measuring system for on-line estimation of Lithium-ion battery cells' internal impedance By Ioannis BOTAS, Olga SOKOLAKI, Emmanuel TATAKIS	[View] [Download]
Abstract: Nowadays, there is a rapid increase in the use of Lithium-Ion batteries for many different applications, due to their superiority in terms of energy density, efficiency, and self-discharge rate. In this paper, a high-performance system for estimation of Lithium-ion battery cells' internal impedance is presented. The main concept lies in the excitation of cells through a multi-sine controlled current signal, instead of using the time-consuming sequential harmonic injection. The proposed technique was implemented for a LiFePO4, 3.2V/30Ah battery cell through a bi-directional power converter, for integrating both charging and discharging capability. A laboratory prototype of this converter was designed and implemented, to investigate theoretical assumptions. The experimental results are eventually analyzed, to evaluate the influence of the various experimental conditions on the cell internal impedance.

	Battery pack thermal management using phase change materials for small electric vehicles By Mohammed MASHAQI, Nassim RIZOUG, Cherif LAROUCI, Mustapha KARKRI, Mahamadou Abdou TANKARI	[View] [Download]
Abstract: Lithium-ion batteries are crucial in automotive applications due to their high energy storage capacity. However, batteries require thermal management to mitigate the negative effects of low, high, and non-uniform temperatures. In this study, we propose a novel battery pack thermal management system based on phase change materials (PCMs) for use in small electric vehicles. PCMs are promising for thermal management systems because of their high thermal energy storage capacity at a constant temperature and their low cost. However, their low thermal conductivity poses a significant challenge. To address this issue, aluminum honeycomb panels are incorporated to the PCM as a PCM heat transfer enhancement technique. This research investigates the impact of using PCM as thermal management system and analyzes the evolution of battery temperature over time with and without PCM under various ambient temperatures. Additionally, the effect of adding an external insulation to the battery pack is examined. The results demonstrate that integrating PCMs between every two battery rows in the pack reduces the battery temperature by 9.8°C compared to the scenario without a thermal management system. Furthermore, At 40°C ambient temperature, adding external insulation reduces the battery temperature by 1.6°C with PCM and by 2.25°C without PCM, both compared to uninsulated cases. These materials shows its potential to serve as an alternative to some traditional cooling methods that rely on fans and pumps.

	Optimized Estimation of Battery ParametersCapacity, Resistances and SOC for ElectricVehicles: A Hybrid Approach Based onGenetic Algorithm and Artificial Intelligence By Jamila HEMDANI, Laid DEGAA, Nassim RIZOUG, Moez SOLTANI, Achraf TELMOUDI, Abdelkader CHAARI	[View] [Download]
Abstract: Index Terms\_AI-Enhanced Battery Modeling forElectric Vehicles: Real-Time Parameter Optimization andState EstimationAbstract\_In this paper, we present a method foroptimizing the key parameters of an equivalent electricalmodel of a battery (Rohmic, R1, C1) and its capacity (Cbat)using advanced artificial intelligence techniques. The goalis to improve the accuracy of the estimation of the State ofCharge (SOC) and State of Health (SOH). We introducea dynamic optimization approach where resistances andcapacitances are adjusted at each time step, while Cbatis optimized over a full cycle. The results demonstrate asignificant improvement in terms of reducing predictionerrors.