Scalable and De-centralized Battery Management System for Parallel Operation of Multiple Battery Packs

Maitreya, Shreyas; Jain, Harshit; Paliwal, Priyanka

doi:10.1109/iemre52042.2021.9386861

Cited by 18 publications

(6 citation statements)

References 6 publications

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“…It requires a separate pack management system operating as a master and battery management systems in each of the battery packs configured as slaves. This significantly affects the scalability of such systems as the number of battery packs that can be connected in parallel is completely dependent on the capacity of the master [12], [25].…”

Section: Operation Planning Of Battery Management Systemsmentioning

confidence: 99%

Review of Battery Types and Application to Wind Power Generation System

POPA,

CHIABURU,

ISAC

2023

JMTE

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The paper discusses diverse energy storage technologies, highlighting the limitations of lead-acid batteries and the emergence of cleaner alternatives such as lithium-ion batteries. It covers battery inspections, factors affecting battery life, and repurposing retired batteries. Additionally, it addresses challenges in wind power generation and the successful application of LL-type VRLA batteries in stabilizing power fluctuations.

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Section: Operation Planning Of Battery Management Systemsmentioning

confidence: 99%

Review of Battery Types and Application to Wind Power Generation System

POPA,

CHIABURU,

ISAC

2023

JMTE

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“…If, the power 𝑃 𝑐ℎ𝑔 (𝑡) and 𝑃 𝑑𝑖𝑠 (𝑡) are the charge load while the battery is being charged and discharged, 𝑉 𝑜𝑐 = Open circuit voltage, and 𝑅𝑖 = Internal resistance of the battery then the discharge current and charge current of the battery can be determined by using (4) [21]- [23].…”

Section: Battery and Battery Management Systemsmentioning

confidence: 99%

Dynamic programming-based control system development for advanced electric power drive

Wadkar,

Patil,

Dhanvijay

et al. 2023

IJPEDS

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An efficient method for raising the effectiveness and performance of fuel cell electric vehicles (FCEVs) is the dynamic programming controller (DPC). By using real-time data to optimize the control inputs, FCEVs can achieve higher levels of efficiency and reduce their environmental impact. The DPC algorithm works by solving an optimization problem at each time step, based on the current state of the vehicle and its environment. The optimal control inputs are then applied to the vehicle to achieve the desired performance criteria. This paper presents the study that utilized MATLAB/Simulink to design, model, and simulate DPC for a FCEV. Controlling various components of the fuel cell (FC) with the optimum power requirement is needed for increasing the performance and mileage of the FCEV. It's important to use FC energy as effectively as possible. Having supervisory control over the FCEV's energy consumption and battery charging is necessary for it to produce this output at its best. To use the hydrogen efficiently, a control strategy is designed for energy management in FCEV. The designed control strategies are implemented through simulation using Simulink in MATLAB. The results show prominent performance of dynamic programming (DP) over rule-based controllers.

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“…In battery-based applications, deployment flexibility, efficiency, and maintenance, fault tolerance is already a crucial concern. Furthermore, integrating a BMS for intelligent and state-of-the-art deployment is another crucial factor to consider to address the technological advancement; especially in this industry 4.0 era which is lacking [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23].…”

Section: B Motivation and Contributionmentioning

confidence: 99%

Design, Implementation, and Deployment of Modular Battery Management System for IIoT-Based Applications

2022

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This paper proposes design and implementation of a battery management system (BMS) for the industrial internet of things (IIoT) enabled applications. The hardware and software development of this BMS is briefly presented in this paper. In terms of hardware development, the presented BMS have modular topology and has 1) high fault tolerance and 2) has exceptionally flexible deployment owing to its topology having multiple local management units (LMUs) connected to a central management unit (CMU). This hardware design approach aims to address the overall design efficiency and cost trade-off of BMS deployment. The hardware design efficiency is tested using actual deployment. In terms of fault tolerance using 1 -3 LMUs at fault, the voltage monitoring accuracy is maintained for each LMUs. An average of 0.00017 V, 0.0008 V and 0.001 V voltage difference is yielded for 1, 2, and 3 modules at fault respectively. Additionally, core BMS sub-circuit is tested to verify hardware design efficiency such as the DC-to-DC converter which yielded 92.74%. Furthermore, the CMU is integrated with a wireless communication circuit that enables IIoTbased applications such as the emerging edge-based, and a plethora of intelligent deployment. In terms of software, the presented BMS aims to realize state-of-the-art processing through IIoT based approach. For software testing and verification, the BMS is deployed to an unmanned ground vehicle (UGV). The signal stability is tested for UGV based application at a 3500s deployment time whereas an average of 0.0010V voltage difference is yielded. This is verified using time markers which is further analyzed using softwarebased signal processing and acquisition simulation. Concisely, the proposed BMS aims to converge IIoT applications to its actual deployment. The proposed BMS is designed, implemented, and successfully deployed to test its viability both in the simulation platform and actual deployment.INDEX TERMS Battery management system, edge processing, industrial IoT, lithium-ion, modular architecture.

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Scalable and De-centralized Battery Management System for Parallel Operation of Multiple Battery Packs

Cited by 18 publications

References 6 publications

Review of Battery Types and Application to Wind Power Generation System

Review of Battery Types and Application to Wind Power Generation System

Dynamic programming-based control system development for advanced electric power drive

Design, Implementation, and Deployment of Modular Battery Management System for IIoT-Based Applications

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