A Matlab framework based on a finite volume model suitable for Li-ion battery design, simulation, and control

Consumer electronics, wearable and personal health devices, power networks, microgrids, and hybrid electric vehicles (HEVs) are some of the many applications of lithium-ion batteries. Their optimal design and management are important for safe and profitable operations. The use of accurate mathematical models can help in achieving the best performance. This page provides a parametrizable Matlab framework for battery design, simulation, and control of Li-ion cells or battery packs. Based on the well known, theory-based pseudo-two-dimensional (P2D) model, the framework has been coded by reformulating the set of PDEs describing the cell behavior into a set of DAEs. The time domain is left continuous, while the spatial domain is discretized according to the Finite Volume Method (FVM). The time-adaptive DAE solver IDA is used to solve the resulting set of DAEs.

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• Marcello Torchio
• Lalo Magni
• Bhushan R. Gopaluni
• Richard D.Braatz
• Davide M. Raimondo

If LIONSIMBA Toolbox is used for research purposes, the authors would like to have it mentioned. Here below the necessary information can be found

• Title: LIONSIMBA: A Matlab framework based on a finite volume model suitable for Li-ion battery design, simulation, and control

• Journal: The Electrochemical Society

• Volume: 163

• Number: 7

• Pages: A1192-A1205

• Year: 2016

Download the latest zip package of LIONSIMBA or clone the Git Repository using the following command

$ git clone https://github.com/lionsimbatoolbox/LIONSIMBA.git

Please feel free to use the 'issue' section on GitHub or write to

davide (dot) raimondo (at) unipv (dot) it

or

marcello (dot) torchio01 (at) ateneopv (dot) it

• Feedback-based custom current profile
• New examples
• Handling of input current discontinuities
• Minor changes

• Minor fixes and bug corrections (thanks to Jeesoon Choi for pointing the bugs out)

• The code has been reorganized and some functions have been modularized for a better maintenance.
• Added support in the user's guide for the installation and configuration of the SUNDIALS Matlab interface.

• Added support for analytical Jacobian. LIONSIMBA is now able to derive automatically the analytical form of the Jacobian describing the P2D dynamics. This knowledge is the exploited from the integration process to speed up the resolution of the DAEs. (Thanks to Dr. Sergio Lucia and Prof. Rolf Findeisen for pointing us out the automatic differentiation provided by CasADi toolbox)
• Minor fixes in the examples.

• Fixed bug in multicell simulation (Thanks to Chintan Pathak for pointing out the bug)

• Fixed SOC calculation bug for Fick's diffusion
• Minor fixes