Novel equivalent circuit model for high-energy lithium-ion batteries considering the effect of nonlinear solid-phase diffusion

Li, Changlong; Cui, Naxin; Cui, Zhongrui; Wang, Chunyu; Zhang, Chenghui

doi:10.1016/j.jpowsour.2022.230993

Cited by 30 publications

(4 citation statements)

References 48 publications

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“…The PD of batteries built to tolerate power transients is lower. EV batteries have longer operational cycles than identical HEV batteries [39]. Table 2 summarizes the energy and PD achieved for various methods.…”

Section: Batterymentioning

confidence: 99%

Trends and Challenges in Electric Vehicle Motor Drivelines - A Review

Venkitaraman

Kosuru

2023

Int. j. electr. comput. eng. syst. (Online)

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Considering the need to optimize electric vehicle performance and the impact of efficient driveline configurations in achieving this, a brief study has been conducted. The drivelines of electric vehicles (EV) are critically examined in this survey. Also, promising motor topologies for usage in electric vehicles are presented. Additionally, the benefits and drawbacks of each kind of electric motor are examined from a system viewpoint. The majority of commercially available EV are powered by a permanent magnet motor or single induction type motors and a standard mechanical differential driveline. Considering these, a holistic review has been performed by including driveline configurations and different battery types. The authors suggest that motors be evaluated and contrasted using a standardized driving cycle.

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Section: Batterymentioning

confidence: 99%

Trends and Challenges in Electric Vehicle Motor Drivelines - A Review

Venkitaraman

Kosuru

2023

Int. j. electr. comput. eng. syst. (Online)

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“…ECMs are essentially based on the adaptation of cell voltage behaviour using time-domain (TDM) or frequency-domain (FDM) measurements [10], [11]. More precisely, TDM-based ECMs can streamline the BMS and be helpful in a range of applications [12], [13]. It should be noted that ECM-based methods provide the advantages of high efficiency and low computing power to identify the dynamic and steady-state characteristics of lithium-ion batteries.…”

Section: Introductionmentioning

confidence: 99%

Review of battery models and experimental parameter identification for lithium-ion battery equivalent circuit models

Belmajdoub,

Lajouad,

El Magri

et al. 2024

IJEECS

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The growing use of electric vehicles has led to an ever-increasing demand for efficient and reliable management systems to control the behavior of lithium-ion batteries, especially with respect to heat generation and state-of-charge. Understanding these patterns constitutes a major new challenge for these batteries, as remaining ignorant of their behavior can result in decreased performance, shorter service life and even safety dangers. This review provides an overview of the different modeling techniques applied to simulate battery behavior. Different methods using equivalent electrical circuit models are discussed, covering both simple battery models and more complex equivalent electrical circuit models, with a focus on the 2RC-Thévenin circuit model. In this context, parameter approach methods for these systems are reviewed. In addition, laboratory tests are run to identify the various model parameters for a lithium-ion battery. This comprehensive study is designed to guide scientists and engineers in the selection and use of suitable tools for state-of-charge and battery health studies.

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“…Nevertheless, the limited accuracy of ECMs may produce challenges for further optimization of SOC estimation under variable load condition. In response to this, some scholars 19,20 have developed the enhanced ECM of LIBs considering electrochemical properties to achieve higher SOC estimation precision. However, these models cannot provide thorough understanding of physics-based states information, which are critical for optimal control of the battery behaviors in advanced BMS applications.…”

Section: Introductionmentioning

confidence: 99%

Low‐complexity state of charge and anode potential prediction for lithium‐ion batteries using a simplified electrochemical model‐based observer under variable load condition

Pang

Geng

et al. 2022

Intl J of Energy Research

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The accurate knowledge of the physics-based state of charge (SOC) and anode potential for lithium-ion batteries (LIBs) plays an essential role in the driving range prediction and charge strategy optimization of electric vehicles (EVs). However, the SOC estimation based on empirical equivalent circuit models and the lack of anode potential information makes it challenging in developing advanced battery management systems for EVs. For this reason, this paper proposes a low-complexity SOC and anode potential prediction method for LIBs using a simplified electrochemical model (SEM)-based observer under variable load condition. First, based on the Padé approximation and volume average method, a reduced-order SEM is proposed and verified. Then, a lowcomplexity proportional-integral-differential observer framework incorporating the SEM is developed to obtain the physics-based SOC and anode potential.

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Novel equivalent circuit model for high-energy lithium-ion batteries considering the effect of nonlinear solid-phase diffusion

Cited by 30 publications

References 48 publications

Trends and Challenges in Electric Vehicle Motor Drivelines - A Review

Trends and Challenges in Electric Vehicle Motor Drivelines - A Review

Review of battery models and experimental parameter identification for lithium-ion battery equivalent circuit models

Low‐complexity state of charge and anode potential prediction for lithium‐ion batteries using a simplified electrochemical model‐based observer under variable load condition

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