[Paper Review] Centralized Recursive Optimal Scheduling of Parallel Buck Regulated Battery Modules

Yunfeng Jiang, Abdulelah H. Habib+3 more|arXiv (Cornell University)|Sep 11, 2017

Advanced Battery Technologies Research17 references3 citations

TL;DR

This paper proposes a centralized recursive optimal scheduling method for parallel-connected battery modules with varying open-circuit voltages and impedances, using buck regulators to balance module currents via PWM control. The method uses recursive linear programming to compute optimal voltage adjustments in real time, experimentally demonstrating balanced currents across three modules under time-varying loads, thus minimizing stray currents and maximizing total bus current without requiring explicit knowledge of module parameters.

ABSTRACT

This paper presents a centralized recursive optimal scheduling method for a battery system that consists of parallel connected battery modules with different open circuit voltages and battery impedance characteristics. Examples of such a battery system can be found in second-life, exchangeable or repurposed battery systems in which batteries with different charge or age characteristics are combined to create a larger storage capacity. The proposed method in this paper takes advantage of the availability of buck regulators in the battery management system (BMS) to compute the optimal voltage adjustment of the individual modules to minimize the effect of stray currents between the parallel connected battery modules. Our proposed method recursively computes the optimal current scheduling that balances (equals) each module current and maximize total bus current without violating any of the battery modules operating constraints. Recursive implementation guarantees robust operation as the battery modules operating parameters change as the battery pack (dis)charges or ages. In order to demonstrate the capability of this method in real battery system, an experimental setup of 3 parallel placed battery modules is built. The experimental results validate the feasibility and show the advantages of this current scheduling method in a real battery application, despite the fact that each module may have different impedance, open circuit voltage and charge parameters.

Motivation & Objective

• To address current imbalance in parallel-connected battery modules with differing state-of-charge, impedance, and open-circuit voltage due to aging or manufacturing variation.
• To develop a control strategy that minimizes stray currents between modules by optimally adjusting individual module voltages via buck regulators.
• To enable efficient, safe, and high-performance operation of battery packs in second-life, exchangeable, or repurposed battery systems.
• To design a recursive algorithm that adapts to changing battery parameters during charging/discharging or aging, ensuring robustness.

Proposed method

• A centralized recursive optimal scheduling algorithm is formulated using linear programming to compute the optimal PWM duty cycle for each battery module’s buck regulator.
• The method computes voltage adjustments to balance module currents and maximize total bus current while respecting individual module constraints.
• The algorithm operates recursively, estimating module parameters in real time without requiring explicit knowledge of open-circuit voltage or internal impedance.
• Buck regulators with PWM-driven MOSFETs modulate the output voltage of each battery module to achieve the desired current balancing.
• The system uses an Arduino Uno to read real-time voltage and current via analog pins and communicate with a host computer running MATLAB for scheduling and data logging.
• The recursive formulation enables adaptation to dynamic changes in battery parameters during operation, ensuring robustness over time.

Experimental results

Research questions

• RQ1 How can current imbalance in parallel-connected battery modules with differing electrical characteristics be minimized in real time?
• RQ2 What control strategy enables optimal current balancing across battery modules without explicit knowledge of individual module parameters?
• RQ3 Can a recursive optimization approach maintain current balance under time-varying external loads and changing battery conditions?
• RQ4 How effective is centralized recursive scheduling in balancing module currents in a real experimental setup with three battery modules?

Key findings

• The proposed method successfully balanced the currents of three parallel battery modules with different internal impedances (3 Ω, 4.5 Ω, and 6 Ω) under time-varying external loads.
• Module currents remained closely matched throughout the 700-second experiment, with minimal deviation despite load changes from 10 Ω to 100 Ω and back.
• The highest-impedance module (6 Ω) was fixed at 100% PWM duty cycle, indicating it required the most voltage reduction to balance currents.
• The recursive algorithm adapted in real time to changing load conditions, maintaining current balance with a 5-second ramp-up for increasing PWM to prevent stress.
• Experimental results confirmed the feasibility and effectiveness of the centralized recursive scheduling method in minimizing stray currents and maximizing total bus current.
• The method demonstrated robustness to parameter variations and aging effects, supporting its use in second-life and exchangeable battery systems.