The fusion of EV technology and IoT has introduced a new era of intelligent battery management. It addresses key challenges in EV and battery-powered systems by monitoring, controlling, and optimizing various aspects of battery operation.
Abstract: This study introduces a balancing control strategy that employs an Artificial Neural Network (ANN) to ensure State of Charge (SOC) balance across lithium-ion (Li-ion) battery packs, consistent with the framework of smart battery packs.
The intelligent algorithms are suitable for lithium-ion batteries to address complex, dynamic, and nonlinear characteristics (Zhao et al., 2020). Besides, intelligent algorithms demonstrate enhanced learning capability, fast convergence speed, improved generalization and high accuracy (Xiong et al., 2018b).
By combining EV technology with the Internet of Things (IoT), this paper explores state-of-the-art solutions for comprehensive battery management. The fusion of EV technology and IoT has introduced a new era of intelligent battery management.
[Google Scholar] [CrossRef] Panwar, N.; Singh, S.; Garg, A.; Gupta, A.; Gao, L. Recent advancements in battery management system for Li-ion batteries of electric vehicles: Future role of digital twin, cyber-physical systems, battery swapping technology, and nondestructive testing.
This research holds the potential to transform battery management systems, prolong battery life, and enable smarter energy consumption. EVs need a reliable battery management system (BMS) to monitor the battery state. The SOC is a crucial factor of a BMS that determines the remaining battery energy and the time that it can last before charging.
The optimal strategy for electric vehicles is becoming important. This review provides a summary focusing on optimal battery management. Model predictive control and AI-based approaches were mainly i...
The fusion of EV technology and IoT has introduced a new era of intelligent battery management. It addresses key challenges in EV and battery-powered systems by monitoring, controlling, …
This cyber–physical system allowed for the closer integration of the physical and digital aspects of batteries, resulting in smarter control and a longer lifespan and providing a …
Vector-based control approaches can be used to separate torque and field …
This paper summarized the current research advances in lithium-ion battery …
Lithium-ion batteries are key components of energy storage systems and electric vehicles, and their accurate State of Charge (SOC) estimation is important for battery …
The estimation of state of health (SOH) of a lithium-ion battery (LIB) is of great significance to system safety and economic development. This paper proposes a SOH …
Request PDF | An Intelligent Fault Diagnosis Method for Lithium Battery Systems Based on Grid Search Support Vector Machine | For the safe operation of the electric vehicle, …
Vector-based control approaches can be used to separate torque and field control, the speediness can be expanded by tumbling the magnetic field strength within the …
The Support Vector Machine (SVM) algorithm is a regression approach that operates using a kernel function. ... In Fig. 23, a flowchart detailing their suggested method for …
To solve the problems of non-linear charging and discharging curves in lithium batteries, and uneven charging and discharging caused by multiple lithium batteries in series and parallel, we …
In this work, a decentralized but synchronized real-world system for smart battery management was designed by using a general controller with cloud computing …
This paper summarized the current research advances in lithium-ion battery management systems, covering battery modeling, state estimation, health prognosis, charging …
Over the last few years, an increasing number of battery-operated devices have hit the market, such as electric vehicles (EVs), which have experienced a tremendous global …
The accurate estimation of battery state of charge (SOC) is an important function of the battery management system, and the precise state of battery is estimated …
The goal of this paper is to deliver a comprehensive review of different intelligent approaches and control schemes of the battery management system in electric vehicle …
Over the last few years, an increasing number of battery-operated devices …
ML-driven thermal management not only ensures better battery performance but also helps in extending battery life by mitigating thermal stress, thus making it a promising approach for the efficient operation of …
To solve the problems of non-linear charging and discharging curves in lithium batteries, and …
The fusion of EV technology and IoT has introduced a new era of intelligent battery …
An Intelligent Fault Diagnosis Method for Lithium Battery Systems Based on Grid Search Support Vector Machine Author links open overlay panel Lei Yao a b, Zhanpeng Fang …
This cyber–physical system allowed for the closer integration of the physical and digital aspects of batteries, resulting in smarter control and a longer lifespan and providing a useful framework for future intelligent and …
Lithium-ion batteries have always been a focus of research on new energy vehicles, however, their internal reactions are complex, and problems such as battery aging …
The lithium-ion battery is increasingly critical in the fields of electric vehicles and sustainable energy. ... Residual life prediction of lithium battery based on improved multi …
The optimal strategy for electric vehicles is becoming important. This review provides a summary focusing on optimal battery management. Model predictive control and AI …
Three for the active equalization circuit board, mainly used for the unbalanced state of the single battery equalization charging and discharging control; 4 for the battery pack …
ML-driven thermal management not only ensures better battery performance but also helps in extending battery life by mitigating thermal stress, thus making it a promising …
Abstract: This study introduces a balancing control strategy that employs an Artificial Neural Network (ANN) to ensure State of Charge (SOC) balance across lithium-ion (Li-ion) battery …
Abstract: This study introduces a balancing control strategy that employs an Artificial Neural …