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Consensus-Based Stochastic Control for Model-Free Cell Balancing

delete2021-09-01
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PRE
AI
I
Ilai Bistritz *
N
Nicholas Bambos
DOI:10.1109/TCNS.2021.3058869delete
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Abstract

Abstract

En 中文
Balancing the state of charge (SOC) of the cells improves both the capacity and the health of the battery. State of the art cell balancing algorithms assume highly accurate SOC estimation which can only be achieved using model-based control solutions. Unfortunately, electrochemical models of batteries are complicated and are still not reliable enough. We propose a simple consensus-based cell balancing algorithm that does not assume any knowledge of the electrochemical model of the battery. Instead, our algorithm only uses SOC estimates from online measurements to make sequential balancing decisions. Using martingale techniques, we prove that our algorithm equalizes the SOC of all cells with probability 1 even with very noisy SOC estimates under a general non-i.i.d. noise model. We then analyze the convergence time of our algorithm as a function of the problem parameters. We also prove performance guarantees for the more challenging case where balancing is done while the battery is charging or discharging. Finally, we present simulations that support our theoretical claims and show the reliability of our algorithm. Our model-free cell balancing is easy to implement and therefore is a major step towards making active cell balancing practical.
Keywords:
Battery control
cell balancing
consensus algorithms
martingales
stochastic control

Journal

IEEE Transactions on Control of Network Systems cover
IEEE Transactions on Control of Network Systems
IF:
5
Papers:
1.7K
Citations:
5.8K

Organization

S
Stanford University
Scholars:
3.7K
Papers: 1.2K
Citations: 0
Cited Papers

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