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<p>The inconsistency between power battery cells can seriously restrict the energy utilization efficiency of the battery pack, accelerate the aging of power batteries, and even significantly increase the risk of thermal runaway. Aiming at this inconsistency, an active equilibrium scheme combining dynamic programming (DP) and model predictive control (MPC) is proposed. Firstly, the topology circuit of the bidirectional flyback transformer with rapid equalization speed is built, and then a system prediction model is established through MPC to achieve rolling optimization. Finally, DP is used to solve the cost function in conditional scenarios to obtain the global optimal current control at the current time, and the system model is used to predict the state changes of multiple sampling periods to achieve an online correction of the balanced current. The algorithm improves the overall equalization efficiency and reduces the energy loss while considering the battery charging and discharging efficiency and equalizer efficiency to ensure the rapid and consistent convergence of each battery’s SOC. Simulation and experimental results show that this strategy can quickly and effectively correct the energy inconsistency of lithium battery packs under various charging and discharging conditions, thereby greatly improving the battery pack’s balance efficiency and energy utilization.</p>

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Research on DP-MPC control strategy based on active equalization system of bidirectional flyback transformer

  • 期刊论文

  • 发表日期：

    2025年8月6日

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  • Yingzhe Kan,
  • Min Yang,
  • Run Qian,
  • Wei Jiang,
  • Yong He,
  • Liang Zhang

摘要

The inconsistency between power battery cells can seriously restrict the energy utilization efficiency of the battery pack, accelerate the aging of power batteries, and even significantly increase the risk of thermal runaway. Aiming at this inconsistency, an active equilibrium scheme combining dynamic programming (DP) and model predictive control (MPC) is proposed. Firstly, the topology circuit of the bidirectional flyback transformer with rapid equalization speed is built, and then a system prediction model is established through MPC to achieve rolling optimization. Finally, DP is used to solve the cost function in conditional scenarios to obtain the global optimal current control at the current time, and the system model is used to predict the state changes of multiple sampling periods to achieve an online correction of the balanced current. The algorithm improves the overall equalization efficiency and reduces the energy loss while considering the battery charging and discharging efficiency and equalizer efficiency to ensure the rapid and consistent convergence of each battery’s SOC. Simulation and experimental results show that this strategy can quickly and effectively correct the energy inconsistency of lithium battery packs under various charging and discharging conditions, thereby greatly improving the battery pack’s balance efficiency and energy utilization.