Optimization Tool for the Characterization of Electric Vehicle Battery Packs

Peter Wilson; Chris Vagg

doi:10.1109/DMC55175.2022.9906467

Optimization Tool for the Characterization of Electric Vehicle Battery Packs

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

Abstract

The use of vehicle scale data for the parameter characterization of electric vehicle battery packs is a challenging topic. This paper describes the implementation of a design tool that carries out both simulated annealing and genetic optimization of model parameters for a modified Nernst Open Circuit Voltage Battery model (K0, K1, K2, K3), concurrently with the dynamic transient model parameters (R0,R1,RP,C1,CP) and pack level parameters including the initial state of charge and capacity (SOCINIT and AH). This paper describes the model for the battery pack implemented in the Saber simulator and the optimization tool (written in TCL-TK) also integrated with the Saber simulator. Results were collected from rolling road tests of of a BMW i8 to validate the fidelity of the model.

Original language	English
Title of host publication	2022 IEEE Design Methodologies Conference, DMC 2022
Publisher	IEEE
ISBN (Electronic)	9781665479998
DOIs	https://doi.org/10.1109/DMC55175.2022.9906467
Publication status	Published - 2 Sep 2022
Event	2022 IEEE Design Methodologies Conference, DMC 2022 - Bath, UK United Kingdom Duration: 1 Sep 2022 → 2 Sep 2022

Publication series

Name	2022 IEEE Design Methodologies Conference, DMC 2022

Conference

Conference	2022 IEEE Design Methodologies Conference, DMC 2022
Country/Territory	UK United Kingdom
City	Bath
Period	1/09/22 → 2/09/22

ASJC Scopus subject areas

Electrical and Electronic Engineering
Control and Optimization
Artificial Intelligence
Energy Engineering and Power Technology

Access to Document

10.1109/DMC55175.2022.9906467

Cite this

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title = "Optimization Tool for the Characterization of Electric Vehicle Battery Packs",

abstract = "The use of vehicle scale data for the parameter characterization of electric vehicle battery packs is a challenging topic. This paper describes the implementation of a design tool that carries out both simulated annealing and genetic optimization of model parameters for a modified Nernst Open Circuit Voltage Battery model (K0, K1, K2, K3), concurrently with the dynamic transient model parameters (R0,R1,RP,C1,CP) and pack level parameters including the initial state of charge and capacity (SOCINIT and AH). This paper describes the model for the battery pack implemented in the Saber simulator and the optimization tool (written in TCL-TK) also integrated with the Saber simulator. Results were collected from rolling road tests of of a BMW i8 to validate the fidelity of the model.",

author = "Peter Wilson and Chris Vagg",

note = "Funding Information: This work was partially funded by the Digital Engineering, Technology and Innovation Programme (DETI) of the West of England Combined Authority (WECA) ; 2022 IEEE Design Methodologies Conference, DMC 2022 ; Conference date: 01-09-2022 Through 02-09-2022",

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doi = "10.1109/DMC55175.2022.9906467",

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AU - Vagg, Chris

N1 - Funding Information: This work was partially funded by the Digital Engineering, Technology and Innovation Programme (DETI) of the West of England Combined Authority (WECA)

PY - 2022/9/2

Y1 - 2022/9/2

N2 - The use of vehicle scale data for the parameter characterization of electric vehicle battery packs is a challenging topic. This paper describes the implementation of a design tool that carries out both simulated annealing and genetic optimization of model parameters for a modified Nernst Open Circuit Voltage Battery model (K0, K1, K2, K3), concurrently with the dynamic transient model parameters (R0,R1,RP,C1,CP) and pack level parameters including the initial state of charge and capacity (SOCINIT and AH). This paper describes the model for the battery pack implemented in the Saber simulator and the optimization tool (written in TCL-TK) also integrated with the Saber simulator. Results were collected from rolling road tests of of a BMW i8 to validate the fidelity of the model.

AB - The use of vehicle scale data for the parameter characterization of electric vehicle battery packs is a challenging topic. This paper describes the implementation of a design tool that carries out both simulated annealing and genetic optimization of model parameters for a modified Nernst Open Circuit Voltage Battery model (K0, K1, K2, K3), concurrently with the dynamic transient model parameters (R0,R1,RP,C1,CP) and pack level parameters including the initial state of charge and capacity (SOCINIT and AH). This paper describes the model for the battery pack implemented in the Saber simulator and the optimization tool (written in TCL-TK) also integrated with the Saber simulator. Results were collected from rolling road tests of of a BMW i8 to validate the fidelity of the model.

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Optimization Tool for the Characterization of Electric Vehicle Battery Packs

Abstract

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