Multi-objective optimal design of lithium-ion battery packs based on evolutionary algorithms

Lithium-battery energy storage systems (LiBESS) are increasingly being used on electric mobility and stationary applications. Despite its increasing use and improvements of the technology there are still challenges associated with cost reduction, increasing lifetime and capacity, and higher safety....

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Published inJournal of power sources Vol. 267; pp. 288 - 299
Main Authors Severino, Bernardo, Gana, Felipe, Palma-Behnke, Rodrigo, Estévez, Pablo A., Calderón-Muñoz, Williams R., Orchard, Marcos E., Reyes, Jorge, Cortés, Marcelo
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.12.2014
Elsevier
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Abstract Lithium-battery energy storage systems (LiBESS) are increasingly being used on electric mobility and stationary applications. Despite its increasing use and improvements of the technology there are still challenges associated with cost reduction, increasing lifetime and capacity, and higher safety. A correct battery thermal management system (BTMS) design is critical to achieve these goals. In this paper, a general framework for obtaining optimal BTMS designs is proposed. Due to the trade-off between the BTMS's design goals and the complex modeling of thermal response inside the battery pack, this paper proposes to solve this problem using a novel Multi-Objective Particle Swarm Optimization (MOPSO) approach. A theoretical case of a module with 6 cells and a real case of a pack used in a Solar Race Car are presented. The results show the capabilities of the proposal methodology, in which improved designs for battery packs are obtained. •An optimization methodology for the battery thermal management design is proposed.•The methodology is based on multi-objective PSO and multi-physics simulations.•A theoretical case shows the trade-off between temperature operation and area.•A real battery pack based on pouch cells for a solar car was designed.•A novel battery packaging design framework is able to find better solutions.
AbstractList Lithium-battery energy storage systems (LiBESS) are increasingly being used on electric mobility and stationary applications. Despite its increasing use and improvements of the technology there are still challenges associated with cost reduction, increasing lifetime and capacity, and higher safety. A correct battery thermal management system (BTMS) design is critical to achieve these goals. In this paper, a general framework for obtaining optimal BTMS designs is proposed. Due to the trade-off between the BTMS's design goals and the complex modeling of thermal response inside the battery pack, this paper proposes to solve this problem using a novel Multi-Objective Particle Swarm Optimization (MOPSO) approach. A theoretical case of a module with 6 cells and a real case of a pack used in a Solar Race Car are presented. The results show the capabilities of the proposal methodology, in which improved designs for battery packs are obtained. •An optimization methodology for the battery thermal management design is proposed.•The methodology is based on multi-objective PSO and multi-physics simulations.•A theoretical case shows the trade-off between temperature operation and area.•A real battery pack based on pouch cells for a solar car was designed.•A novel battery packaging design framework is able to find better solutions.
Lithium-battery energy storage systems (LiBESS) are increasingly being used on electric mobility and stationary applications. Despite its increasing use and improvements of the technology there are still challenges associated with cost reduction, increasing lifetime and capacity, and higher safety. A correct battery thermal management system (BTMS) design is critical to achieve these goals. In this paper, a general framework for obtaining optimal BTMS designs is proposed. Due to the trade-off between the BTMS's design goals and the complex modeling of thermal response inside the battery pack, this paper proposes to solve this problem using a novel Multi-Objective Particle Swarm Optimization (MOPSO) approach. A theoretical case of a module with 6 cells and a real case of a pack used in a Solar Race Car are presented. The results show the capabilities of the proposal methodology, in which improved designs for battery packs are obtained.
Author Reyes, Jorge
Cortés, Marcelo
Orchard, Marcos E.
Palma-Behnke, Rodrigo
Severino, Bernardo
Gana, Felipe
Estévez, Pablo A.
Calderón-Muñoz, Williams R.
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  surname: Severino
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  surname: Gana
  fullname: Gana, Felipe
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  givenname: Rodrigo
  surname: Palma-Behnke
  fullname: Palma-Behnke, Rodrigo
  email: rodpalma@cec.uchile.cl
  organization: Department of Electrical Engineering, Universidad de Chile, Av. Tupper 2007, Santiago, Chile
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  givenname: Pablo A.
  surname: Estévez
  fullname: Estévez, Pablo A.
  organization: Department of Electrical Engineering, Universidad de Chile, Av. Tupper 2007, Santiago, Chile
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  givenname: Williams R.
  surname: Calderón-Muñoz
  fullname: Calderón-Muñoz, Williams R.
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  organization: Department of Electrical Engineering, Universidad de Chile, Av. Tupper 2007, Santiago, Chile
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  givenname: Jorge
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  fullname: Reyes, Jorge
  organization: Energy Center, Universidad de Chile, Av. Tupper 2007, Santiago, Chile
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  givenname: Marcelo
  surname: Cortés
  fullname: Cortés, Marcelo
  organization: Department of Electrical Engineering, Universidad de Antofagasta, Av. Angamos 601, Antofagasta, Chile
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Keywords Multi-objective particle swarm optimization
Lithium-battery energy storage systems
Battery cell arrangement
Battery thermal management system
Multiphysics simulation
Optimal design
Lithium ion batteries
Battery storage plants
Evolutionary algorithm
Alkaline storage battery
Multiobjective programming
Theoretical study
Secondary cell
Modeling
Particle swarm optimization
Lithium battery
Experimental design
Battery management systems
System simulation
Mathematical model
Chemometrics
Energy storage
Language English
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Snippet Lithium-battery energy storage systems (LiBESS) are increasingly being used on electric mobility and stationary applications. Despite its increasing use and...
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SubjectTerms Applied sciences
Battery
Battery cell arrangement
Battery thermal management system
Design engineering
Direct energy conversion and energy accumulation
Electrical engineering. Electrical power engineering
Electrical power engineering
Electrochemical conversion: primary and secondary batteries, fuel cells
Energy
Energy. Thermal use of fuels
Exact sciences and technology
Lithium-battery energy storage systems
Lithium-ion batteries
Modules
Multi-objective particle swarm optimization
Multiphysics simulation
Optimal design
Optimization
Proposals
Race
Thermal management
Transport and storage of energy
Title Multi-objective optimal design of lithium-ion battery packs based on evolutionary algorithms
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