Range Maximisation of Electric Vehicles through Active Cell Balancing using Reachability Analysis

Hoekstra, F.S.J.; Bergveld, Henk Jan; Donkers, M.C.F.

doi:10.23919/acc.2019.8814748

Cited by 13 publications

(19 citation statements)

References 14 publications

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“…In this brief, we extend the work of Hoekstra et al [12], [13], in two ways. Compared to [12], we propose a more robust and faster approach to find a rangemaximizing optimal-control strategy for active cell balancing.…”

Section: Introductionmentioning

confidence: 91%

“…Moreover, having acknowledged violation of the voltage limit as the key indicator for stopping current flow, it is important to see that literature often applies inaccurate battery models [3], i.e., without dynamical overpotential dynamics and with linear open-circuit voltage relations [11]. In previous work of Hoekstra et al [12], [13], range maximization has been posed as the sole objective of active cell balancing. First, an approach has been presented in [12] that could retrieve the maximum possible range and its corresponding balancing currents for a particular power cycle.…”

Section: Introductionmentioning

confidence: 99%

“…In previous work of Hoekstra et al [12], [13], range maximization has been posed as the sole objective of active cell balancing. First, an approach has been presented in [12] that could retrieve the maximum possible range and its corresponding balancing currents for a particular power cycle. From these results, a realtime computable Model-Predictive-Control (MPC) strategy has been derived [13].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal Control of Active Cell Balancing: Extending the Range and Useful Lifetime of a Battery Pack

Hoekstra

Bergveld

Donkers

2022

IEEE Trans. Contr. Syst. Technol.

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Section: Introductionmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Optimal Control of Active Cell Balancing: Extending the Range and Useful Lifetime of a Battery Pack

Hoekstra

Bergveld

Donkers

2022

IEEE Trans. Contr. Syst. Technol.

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“…Cell balancing is a technology that has arisen to address these issues [25][26][27][28][29][30][31][32][33][34][35][36]. Cellbalancing methods can be classified into dissipative and nondissipative methods, with the difference being whether the balancing method relies on resistive elements, i.e., energydissipative, or charge transfer, i.e., nondissipative [37].…”

Section: Introductionmentioning

confidence: 99%

“…MPC-based active cell balancing has also been widely studied in the literature [1][2][3]27,[38][39][40][41]. In [1], an MPC controller was developed and evaluated for active cell balancing to extend the range capability of EV batteries.…”

Section: Introductionmentioning

confidence: 99%

Reinforcement Learning-Based Event-Triggered Active-Battery-Cell-Balancing Control for Electric Vehicle Range Extension

Flessner,

Chen,

Xiong

2024

Electronics

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Optimal control techniques such as model predictive control (MPC) have been widely studied and successfully applied across a diverse field of applications. However, the large computational requirements for these methods result in a significant challenge for embedded applications. While event-triggered MPC (eMPC) is one solution that could address this issue by taking advantage of the prediction horizon, one obstacle that arises with this approach is that the event-trigger policy is complex to design to fulfill both throughput and control performance requirements. To address this challenge, this paper proposes to design the event trigger by training a deep Q-network reinforcement learning agent (RLeMPC) to learn the optimal event-trigger policy. This control technique was applied to an active-cell-balancing controller for the range extension of an electric vehicle battery. Simulation results with MPC, eMPC, and RLeMPC control policies are presented along with a discussion of the challenges of implementing RLeMPC.

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Impact of battery cell imbalance on electric vehicle range

Chen¹,

Zhou²,

Zhou³

et al. 2022

Green Energy and Intelligent Transportation

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Range Maximisation of Electric Vehicles through Active Cell Balancing using Reachability Analysis

Cited by 13 publications

References 14 publications

Optimal Control of Active Cell Balancing: Extending the Range and Useful Lifetime of a Battery Pack

Optimal Control of Active Cell Balancing: Extending the Range and Useful Lifetime of a Battery Pack

Reinforcement Learning-Based Event-Triggered Active-Battery-Cell-Balancing Control for Electric Vehicle Range Extension

Impact of battery cell imbalance on electric vehicle range

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