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

Lin, Xinfan; Fu, Huan; Pérez, Hector E.; Siege, Jason B.; Stefanopoulou, Anna G.; Ding, Yi; Castanier, Matthew P.

doi:10.2516/ogst/2012075

Cited by 97 publications

(58 citation statements)

References 16 publications

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“…Different observability scalar quantifications for both linear and nonlinear systems have been proposed by many references 1 In this paper, the prime symbol indicates transpose. and a short overview can be found in [4].…”

Section: IImentioning

confidence: 99%

“…Taking as an example the observable sensor combinations as in [1], different sensor combinations will be seen as equal as they all give an observable system.…”

Section: Introductionmentioning

confidence: 99%

“…In [1], observability matrix of a battery string state space thermal model was used to determine the minimum number and location of sensors for estimating temperature of individual battery cells. However, only the number of observable combinations was given, whereas the information whether particular combinations might be better than the others, or vice versa, was neither analyzed nor quantified.…”

Section: Introductionmentioning

confidence: 99%

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Observability degree criteria evaluation for temperature observability in a battery string towards optimal thermal sensors placement

Lystianingrum

Hredzak

Agelidis

et al. 2014

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)

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Temperature measurement in battery strings is most critical not just for safety reasons but also to restrain operating conditions that would reduce the battery lifetime. However, placing a thermal sensor in each individual battery cell within a battery string implies cost and space. In this paper, the optimal number and location of thermal sensors in a forced-cooled battery string is discussed. Different observability Gramianbased observability criteria are used to evaluate and compare observability degree of placement of different number and different combinations of sensors locations in the battery string. The observability degree is further verified by evaluating the observer performance for the different sensor locations. The most suitable observability criteria to ascertain the optimal location of such thermal sensors are recommended.

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Section: IImentioning

confidence: 99%

“…Taking as an example the observable sensor combinations as in [1], different sensor combinations will be seen as equal as they all give an observable system.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Observability degree criteria evaluation for temperature observability in a battery string towards optimal thermal sensors placement

Lystianingrum

Hredzak

Agelidis

et al. 2014

2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP)

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“…The overall aim is to have a combination of active monitoring of the surface temperature in combination with in situ modelling of the internal temperature and active control of the thermal management system. Research efforts are being directed towards this aim [101][102][103].…”

Section: Discussionmentioning

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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“…The electrical characteristics may be described by simple equivalent circuit models (ECM) [11][12][13][14][15][16] or PDE based models [17][18][19][20], whilst the thermal aspects can be captured by simple two state models [21][22][23] or complex thermal models that describe the temperature distribution of the cell [24][25][26]. Although the more complex models are highly accurate, they are difficult to parametrise and require large computational capabilities, rendering them unsuitable for control oriented applications such as BMS modelling.…”

Section: Introductionmentioning

confidence: 99%

Innovative Method for Simultaneous Electrical and Thermal Parametrisation of Automotive Batteries

Grandjean

McGordon

Widanage

2017

2017 IEEE Vehicle Power and Propulsion Conference (VPPC)

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

Cited by 97 publications

References 16 publications

Observability degree criteria evaluation for temperature observability in a battery string towards optimal thermal sensors placement

Observability degree criteria evaluation for temperature observability in a battery string towards optimal thermal sensors placement

Theoretical Modelling Methods for Thermal Management of Batteries

Innovative Method for Simultaneous Electrical and Thermal Parametrisation of Automotive Batteries

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