Dynamic Thermal Model of Li-Ion Battery for Predictive Behavior in Hybrid and Fuel Cell Vehicles

Park, Chanwoo; Jaura, Arun

doi:10.4271/2003-01-2286

Cited by 126 publications

(79 citation statements)

References 3 publications

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“…The single cell cylindrical battery thermal model in Equation (1) can be scaled up to a battery cluster model by considering cell to cell heat conduction [21] and heat balance of the flowing coolant [6,11], as shown in Figure 6. As shown in Figure 6, the cluster can be simplified by considering cells that are connected in series with tabs and are geometrically arranged in a row configuration along the coolant flow path.…”

Section: Scalable Battery Cluster Thermal Modelmentioning

confidence: 99%

“…A cylindrical battery is modeled with two states, one for the surface temperature T s and the other for the core temperature T c , as shown in Figure 1 (adopted from [11]). Single cell lumped resistance thermal model.…”

Section: Lumped Thermal Model Of a Cylindrical Lithium-ion Batterymentioning

confidence: 99%

“…In order for the observer to work well, the model parameters should be as accurate as possible. Since all these parameters are lumped parameters, textbook values found by correlating to the geometry of the battery and physical properties of all its components [11] may not be accurate. The parameters can also be determined based on data obtained from designed experiments with extra measurements in a offline fashion [10,11].…”

Section: Introductionmentioning

confidence: 99%

“…A second order lumped thermal model for cylindrical lithium ion batteries have been proposed in [11]. Such simplified model captures both the surface and core temperatures of the cell, and is efficient enough for onboard application.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Parameterization and Observability Analysis of Scalable Battery Clusters for Onboard Thermal Management

Lin

Pérez

et al. 2013

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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Section: Scalable Battery Cluster Thermal Modelmentioning

confidence: 99%

Section: Lumped Thermal Model Of a Cylindrical Lithium-ion Batterymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Parameterization and Observability Analysis of Scalable Battery Clusters for Onboard Thermal Management

Lin

Pérez

et al. 2013

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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“…Another factor that affects the lifetime of an ESS is the cell temperature distribution. The cell temperature difference must be limited to below 5 °C to maximise the ESS lifetime [22,23]. Large temperature non-uniformity in the ESS pack reduces the overall cell lifespan as well as available cell capacity [24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Theoretical Modelling Methods for Thermal Management of Batteries

Shabani¹,

Biju²

2015

Energies

104

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Abstract:The main challenge associated with renewable energy generation is the intermittency of the renewable source of power. Because of this, back-up generation sources fuelled by fossil fuels are required. In stationary applications whether it is a back-up diesel generator or connection to the grid, these systems are yet to be truly emissions-free. One solution to the problem is the utilisation of electrochemical energy storage systems (ESS) to store the excess renewable energy and then reusing this energy when the renewable energy source is insufficient to meet the demand. The performance of an ESS amongst other things is affected by the design, materials used and the operating temperature of the system. The operating temperature is critical since operating an ESS at low ambient temperatures affects its capacity and charge acceptance while operating the ESS at high ambient temperatures affects its lifetime and suggests safety risks. Safety risks are magnified in renewable energy storage applications given the scale of the ESS required to meet the energy demand. This necessity has propelled significant effort to model the thermal behaviour of ESS. Understanding and modelling the thermal behaviour of these systems is a crucial consideration before designing an efficient thermal management system that would operate safely and extend the lifetime of the ESS. This is vital in order to eliminate intermittency and add value to renewable sources of power. This paper concentrates on reviewing theoretical approaches used to simulate the operating temperatures of ESS and the subsequent endeavours of modelling thermal management systems for these systems. The intent of this review is to present some of the different methods of modelling the thermal behaviour of ESS highlighting the advantages and disadvantages of each approach. OPEN ACCESSEnergies 2015, 8 10154

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Liquid cooling based on thermal silica plate for battery thermal management system

et al. 2017

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Summary To achieve safe, long lifetime, and high‐performance lithium‐ion batteries, a battery thermal management system (BTMS) is indispensable. This is especially required for enabling fast charging‐discharging and in aggressive operating conditions. In this research, a new type of battery cooling system based on thermal silica plates has been designed for prismatic lithium‐ion batteries. Experimental and simulations are combined to investigate the cooling capability of the BTMS associated to different number of cooling channels, flow rates, and flow directions while at different discharge C‐rates. Results show that the maximum temperature reached within the battery decreases as the amount of thermal silica plates and liquid channels increases. The flow direction had no significant influence on the cooling capability. While the performance obviously improves with the increase in inlet flow rate, after a certain threshold, the gain reduces strongly so that it does not anymore justify the higher energy cost. Discharged at 3 C‐rate, an inlet flow rate of 0.1 m/s was sufficient to efficiently cool down the system; discharged at 5 C‐rate, the optimum inlet flow rate was 0.25 m/s. Simulations could accurately reproduce experimental results, allowing for an efficient design of the liquid‐cooled BTMS.

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Dynamic Thermal Model of Li-Ion Battery for Predictive Behavior in Hybrid and Fuel Cell Vehicles

Cited by 126 publications

References 3 publications

Parameterization and Observability Analysis of Scalable Battery Clusters for Onboard Thermal Management

Parameterization and Observability Analysis of Scalable Battery Clusters for Onboard Thermal Management

Theoretical Modelling Methods for Thermal Management of Batteries

Liquid cooling based on thermal silica plate for battery thermal management system

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