Battery CCCV charging model

This CC-CV charger model with a Li-ion Battery can run quickly, and is thus suitable for lifetime simulations.

This is a matlab simulink model of Li-ion battery with fast CCCV charging mode.

'CCCV_RUL_SOCrange.m' is the code to run a Simulink model and store the data for a range of operations automatically.

'CCCV_BatteryCell_RunDirect.slx' is a Simulink model that can be run directly without any code.

‘CCCV_BatteryCell_FullChargerModel.slx’ is provided for study purposes, wherein contains the old battery and charger models that have been removed from the library.

Subfolder ‘Code_m file for parallel computing and data storage’ contains the code to simulate the model and store the data in a given operation range. 'parsim' is used for parallel computing.

Note that in Matlab has released a new CC-CV charger from 2022b version.

Note that the voltage value (change in Bolck ‘Voltage’) that can activate different charging modes are NOT the same to all batteries. To see the curves for different modes, the voltage value setting is subject to the battery parameters (change in Bolck 'Battery') and charging/discharging current (change in Bolck 'Relay').

Contact the author by [e-mail]

More detailed manual can also be found at: https://github.com/Xie-Jiahang/TII_HIRUL_OPF

Battery parameters

Related works:

1. T-shape data and probabilistic remaining useful life prediction for Li-ion batteries using multiple non-crossing quantile long short-term memory

This paper introduces and formalizes the concept of T-shape data, which arises in several engineering and natural contexts, where the data are richer at initial stages than the data in the following time. The proposed T-shape data with unbalanced structure over time arises owing to authority changes and privacy limitations.

2. Health-Informed Lifespan-Oriented Circular Economic Operation of Li-Ion Batteries

This article proposes a dynamic framework for health-informed optimal power flow (OPF) to reach the battery expected lifespan by offering the optimal feasible operation space. The expected service lifespan is achieved if the battery’s daily working condition is confined within such evolving feasible domains throughout its service time. Economical operation of the battery is scheduled based on OPF that integrates such feasible domains upon convexification for higher computational efficiency.

3. Voltage feasibility-constrained peer-to-peer energy trading with polytopic injection domains

Peer-to-peer (P2P) energy trading is an important energy market concept that improves the utilization of distributed energy resources and promotes the integration of energy storage technologies in distribution grids. It is challenging to satisfy the grid operational feasibility under such decentralized energy markets while enabling fully autonomous prosumer operations. This work develops a self-validation mechanism based on polytopic injection domains that define the allowed/safe region of prosumer power injections, ensuring feasible operation of the distribution grid.

@article{ly2023t, title={T-shape data and probabilistic remaining useful life prediction for Li-ion batteries using multiple non-crossing quantile long short-term memory}, author={Ly, Sel and Xie, Jiahang and Wolter, Franz-Erich and Nguyen, Hung D and Weng, Yu}, journal={Applied Energy}, volume={349}, pages={121355}, year={2023}, publisher={Elsevier} }

@article{xie2022health, title={Health-Informed Lifespan-Oriented Circular Economic Operation of Li-Ion Batteries}, author={Xie, Jiahang and Weng, Yu and Nguyen, Hung D}, journal={IEEE Transactions on Industrial Informatics}, volume={19}, number={3}, pages={2749--2760}, year={2022}, publisher={IEEE} }

@article{sampath2022voltage, title={Voltage feasibility-constrained peer-to-peer energy trading with polytopic injection domains}, author={Sampath, Lahanda Purage Mohasha Isuru and Weng, Yu and Wolter, Franz-Erich and Gooi, Hoay Beng and Nguyen, Hung Dinh}, journal={Electric Power Systems Research}, volume={212}, pages={108591}, year={2022}, publisher={Elsevier} }