State‐of‐Power Estimation of Li‐Ion Batteries Considering the Battery Surface Temperature

Liu, Xintian; He, Ye; Zeng, Guojian; Zhang, Jiangfeng; Zheng, Xinxin

doi:10.1002/ente.201700680

Cited by 16 publications

(5 citation statements)

References 21 publications

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“…Besides, the influence on the surface temperature of the battery is provided, which applies a constrained multiparameter algorithm (CMPA) to estimate the SOE of batteries. 28 Battery SOE and SOP are two main parameters in a battery energy storage system, which determines the high-efficiency usage of batteries. The power battery for vehicles is working in practical application, the change of the driving conditions has effects on the online estimation of the SOE.…”

Section: Soe Equalizationmentioning

confidence: 99%

Series‐connected battery equalization system: A systematic review on variables, topologies, and modular methods

2021

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Series-connected lithium battery packs are widely adopted in industries such as electrical vehicles and large-scale energy storage systems. It is necessary to configure an equalization system for them to reduce the inconsistency of single cells, to ensure the battery pack cycle capacity. Although many novel active converters have been proposed for equalization, there still lacks systematic analyses on variables, topologies, and modular methods. Therefore, this paper provides a systematic review on the above aspects. Initially, an overall summary is present on current variables for equalization control. Second, the dominant structures are divided into cell-to-cell, cell-to-pack, and pack-to-pack topologies, and their characteristics are pointed out for comparison. And then, the modular methods, including single-layer-based, multi-layer-based, and hybrid integrations are evaluated via graph theory. Some key issues and potential research directions are given, which are expected to offer assistance on the selection of appropriate variables and topologies for equalization systems in the future.

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Section: Soe Equalizationmentioning

confidence: 99%

Series‐connected battery equalization system: A systematic review on variables, topologies, and modular methods

2021

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“…Jiang et al [6] applied the multi-constraint SoP estimation method under high-temperature conditions, proving that the resulting SoP had good precision. Thermal characteristics of batteries during acceleration or deceleration of electric vehicles are also considered for assessing the temperature effect on SoP improving the estimation accuracy [7]. However, the study lacks the incorporation of the SoC and resistance effects on the resulting SoP.…”

Section: Introductionmentioning

confidence: 99%

Model Development for State-of-Power Estimation of Large-Capacity Nickel-Manganese-Cobalt Oxide-Based Lithium-Ion Cell Validated Using a Real-Life Profile

et al. 2022

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This paper investigates the model development of the state-of-power (SoP) estimation for a 43 Ah large-capacity prismatic nickel-manganese-cobalt oxide (NMC) based lithium-ion cell with a thorough aging investigation of the cells’ internal resistance increase. For a safe operation of the vehicle system, a battery management system (BMS) integrated with SoP estimation functions is crucial. In this study, the developed SoP model used for the estimation of power throughout the lifetime of the cell is coupled with a dual-polarization equivalent-circuit model (DP_ECM) for achieving the precise estimation of desired parameters. The SoP model is developed based on the pulse-trained internal resistance evolution approach, and hence the power is estimated by determining the rate of internal resistance increase. Hybrid pulse power characterization (HPPC) test results are used for extraction of the impedance parameters. In the DP_ECM, Coulomb counting and extended Kalman filter (EKF) state estimation methods are developed for the accurate estimation of the state of charge (SoC) of the cell. The SoP model validation is performed by using both dynamic Worldwide harmonized Light vehicles Test Cycles (WLTC) and static current profiles, achieving promising results with root-mean-square errors (RMSE) of 2% and 1%, respectively.

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“…The two methods above are called direct methods, suitable only for the open‐loop system. [ 34 ] At the same time, indirect methods or adaptive methods are also proposed for the estimation of SOC. The Kalman filter (KF) approach is another well‐known way for obtaining precise battery parameters and a stable SOC.…”

Section: Introductionmentioning

confidence: 99%

Estimation of State of Charge and State of Health of Lithium‐Ion Batteries Based on a New Adaptive Nonlinear Observer

Sakile

Sinha

2021

Advcd Theory and Sims

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Estimation of accurate state of charge (SOC) and state of health (SOH) of lithium‐ion batteries has become more difficult in electric vehicles due to various uncertainties in the battery. The main objective of this paper is to estimate the accurate and robust SOC and SOH of the lithium‐ion battery. Here, a first‐order resistor‐capacitor (RC) electrical equivalent circuit model is considered for the analysis and modeling, an adaptive nonlinear observer (ANO) is proposed to convert nonlinear equations into linearized equations. The transfer function is obtained from the linearized equations to estimate the actual parameters and the internal states of the battery. When comparing the proposed ANO to the conventional method extended Kalman filter, the new ANO gives better dynamic results, less SOC error, and high convergence capability. An extra random variable noise is added to the system; the proposed model is suitable for the SOC at current noise factors. The convergence capability of the observer is analyzed with the linear criterion. The simulation results of the proposed ANO are validated through the MATLAB/Simulink platform under the hybrid pulse power characteristics test.

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State‐of‐Power Estimation of Li‐Ion Batteries Considering the Battery Surface Temperature

Cited by 16 publications

References 21 publications

Series‐connected battery equalization system: A systematic review on variables, topologies, and modular methods

Series‐connected battery equalization system: A systematic review on variables, topologies, and modular methods

Model Development for State-of-Power Estimation of Large-Capacity Nickel-Manganese-Cobalt Oxide-Based Lithium-Ion Cell Validated Using a Real-Life Profile

Estimation of State of Charge and State of Health of Lithium‐Ion Batteries Based on a New Adaptive Nonlinear Observer

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