Research on battery intelligent management and control technology

Intelligent algorithms and control strategies for battery management

This study analyzes and evaluates the role of AI approaches in enhancing the battery management system (BMS) in EVs and guides future researchers in developing emerging BMS technology for sustainable operation and management in EVs.

Research on Intelligent Operation and Maintenance System of Battery

This article first analyzes the application of digital twin technology in battery management, creates an intelligent battery operation and maintenance management and advanced measurement system based on the Internet of Things, and provides a certain reference for improving the detection level of battery operation and maintenance management systems.

Energy and battery management systems for electrical vehicles: A

A control branch known as a "Battery Management System (BMS)" is modeled to verify the operational lifetime of the battery system pack (Pop et al., 2008; Sung and Shin, 2015). For the purposes of safety, fair balancing among the cells of the battery package has to be under instantaneous supervision. The utilization of BMS will provide a robust system

Review Of Artificial Intelligence Based Integration Techniques Of

This research paper analyzes the impact of AI-based algorithms on battery performance, safety, and overall EV operation, and identifies potential research directions for future advancements...

Research progress on efficient battery thermal management

The increasing demand for electric vehicles (EVs) has brought new challenges in managing battery thermal conditions, particularly under high-power operations. This paper provides a comprehensive review of battery thermal management systems (BTMSs) for lithium-ion batteries, focusing on conventional and advanced cooling strategies. The primary objective

Applications of artificial intelligence and cell balancing techniques

BMS optimizes battery via SOC monitoring, cell balancing, and safety control. FLC, SVM, PSO, ANN, and GA algorithms improve SOC estimation accuracy. Cell balancing extends battery life, performance, and safety in EVs.

Intelligent algorithms and control strategies for battery

This study analyzes and evaluates the role of AI approaches in enhancing

Intelligent algorithms and control strategies for battery management

Battery management system (BMS) plays a significant role to improve battery lifespan. This review explores the intelligent algorithms for state estimation of BMS. The thermal management, fault diagnosis and battery equalization are investigated. Various key issues and challenges related to battery and algorithms are identified.

Artificial Intelligence Approaches for Advanced Battery Management

In EV battery management, neural-based networks encompass various approaches, including deep learning, reinforcement learning, and other network architectures, utilized to optimize thermal management, predict battery degradation, and enhance overall battery efficiency and safety. Each of these methodologies plays a crucial role in leveraging data

Employment of Artificial Intelligence (AI) Techniques in Battery

For that purpose, a variety of Artificial Intelligence (AI) techniques have been proposed in the literature to enhance BMS capabilities, such as monitoring, battery state estimation, fault...

Intelligent algorithms and control strategies for battery

Battery management system (BMS) plays a significant role to improve battery

Applications of artificial intelligence and cell balancing techniques

BMS optimizes battery via SOC monitoring, cell balancing, and safety control.

Optimization and intelligent power management control for an

In this paper, a critical issue related to power management control in autonomous hybrid systems is presented. Specifically, challenges in optimizing the performance of energy sources and backup

Research on Battery Safety Management and Protection Technology

In recent years, the operation life of energy storage power station is increasing, and its safety problem has gradually become the focus of the industry. This paper expounds the core technology of safe and stable operation of energy storage power station from two aspects of battery safety management and safety protection, and looks forward to the development trend

Future smart battery and management: Advanced sensing from external

A reliable battery management system (BMS) is critical to fulfill the expectations on the reliability, efficiency and longevity of LIB systems. Recent research progresses have witnessed the emerging technique of smart battery and the associated management system, which can potentially overcome the deficiencies met by traditional BMSs. Motivated

Intelligent algorithms and control strategies for battery management

To address these concerns, an effective battery management system plays a crucial role in enhancing battery performance including precise monitoring, charging-discharging control, heat...

Employment of Artificial Intelligence (AI) Techniques in Battery

For that purpose, a variety of Artificial Intelligence (AI) techniques have been

Intelligent battery management for electric and hybrid electric

The intelligent battery management systems aim at lengthening the lifetime of the battery pack and enhancing the safety of drivers of electric and hybrid electric vehicles. Three major research topics are covered in the paper, state of charge (SoC), state of health (SoH) of the battery pack, and the remaining driving range estimation.

Overview of batteries and battery management for electric vehicles

Until now, it is still a research topic in battery chemistry (Zeng et al., 2017, Real-time online diagnosis can be deemed as one of the most significant concerns on intelligent battery management, especially for autonomous EVs. (1) Thermal Management. Abnormal temperatures may degrade the battery capacity and shorten the service life. Thus, thermal

(PDF) Digital Twin Technology Based Lithium-Ion

On this basis, the design framework of a lithium-ion BMS based on DT is clarified, with the goal of providing guidance and a reference for research into building an intelligent management system

Artificial Intelligence Approaches for Advanced Battery Management

In EV battery management, neural-based networks encompass various approaches, including deep learning, reinforcement learning, and other network architectures, utilized to optimize thermal management, predict battery degradation, and enhance overall battery efficiency and safety. Each of these methodologies plays a crucial role in leveraging

Intelligent Traffic Management and Control Technology

7.1.1 Concept and Development Status of ITMS. Intelligent Traffic Management System (ITMS) is an important part of intelligent transportation systems. Intelligent traffic management is defined as follows: According to the urban road traffic information collection, processing, release, and decision-making process, various advanced technologies and

Research on environmental monitoring and control

This study studies the technology of environmental monitoring and control in an intelligent Internet of Things (IoT) perception. To improve the issue of small coverage and low stability in the

EKENERGY