State of charge estimation for electric vehicle batteries using unscented kalman filtering

He, Wei; Williard, Nicholas; Chen, Chaochao; Pecht, Michael

doi:10.1016/j.microrel.2012.11.010

Cited by 305 publications

(147 citation statements)

References 23 publications

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“…There are a few ways to obtain OCV, in which the stationary method is a direct method and is relatively more accurate. To obtain the relationship between the battery OCV and SOC in the stationary method, the test procedures are performed as follows [30]:…”

Section: Battery Testing Benchmentioning

confidence: 99%

Comparative Research on RC Equivalent Circuit Models for Lithium-Ion Batteries of Electric Vehicles

et al. 2017

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Equivalent circuit models are a hot research topic in the field of lithium-ion batteries for electric vehicles, and scholars have proposed a variety of equivalent circuit models, from simple to complex. On one hand, a simple model cannot simulate the dynamic characteristics of batteries; on the other hand, it is difficult to apply a complex model to a real-time system. At present, there are few systematic comparative studies on equivalent circuit models of lithium-ion batteries. The representative first-order resistor-capacitor (RC) model and second-order RC model commonly used in the literature are studied comparatively in this paper. Firstly, the parameters of the two models are identified experimentally; secondly, the simulation model is built in Matlab/Simulink environment, and finally the output precision of these two models is verified by the actual data. The results show that in the constant current condition, the maximum error of the first-order RC model is 1.65% and the maximum error for the second-order RC model is 1.22%. In urban dynamometer driving schedule (UDDS) condition, the maximum error of the first-order RC model is 1.88%, and for the second-order RC model the maximum error is 1.69%. This is of great instructional significance to the application in practical battery management systems for the equivalent circuit model of lithium-ion batteries of electric vehicles.

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Section: Battery Testing Benchmentioning

confidence: 99%

Comparative Research on RC Equivalent Circuit Models for Lithium-Ion Batteries of Electric Vehicles

et al. 2017

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“…Through the nonlinear model, the mean and variance can be accurate to the nonlinear term of second-order Taylor expansion, so the accuracy of nonlinear filtering is higher. Thus, He et al [41] not only built a joint coulomb counting method and battery voltage model but also introduced the UKF to adjust model parameters, estimated the battery status, and predicted the RUL, which was better than the EKF. Zheng et al [42] built a nonlinear time series prediction model to predict the battery life and adopted the UKF to predict residual.…”

Section: Rul Prognostics Methodologies Based On Filtering Techniquesmentioning

confidence: 99%

Review of the Remaining Useful Life Prognostics of Vehicle Lithium-Ion Batteries Using Data-Driven Methodologies

Guan

2016

Applied Sciences

154

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Lithium-ion batteries are the primary power source in electric vehicles, and the prognosis of their remaining useful life is vital for ensuring the safety, stability, and long lifetime of electric vehicles. Accurately establishing a mechanism model of a vehicle lithium-ion battery involves a complex electrochemical process. Remaining useful life (RUL) prognostics based on data-driven methods has become a focus of research. Current research on data-driven methodologies is summarized in this paper. By analyzing the problems of vehicle lithium-ion batteries in practical applications, the problems that need to be solved in the future are identified.

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“…Hence, sophisticated methods to improve accuracy are needed. This can be done, e.g., by Kalman filters [47]. A detailed overview and comparison of further existing methods is provided by [48].…”

Section: Battery Management Systemmentioning

confidence: 99%

Battery Design for Successful Electrification in Public Transport

et al. 2015

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Abstract:Public transport is an especially promising sector for full electric vehicles due to the high amount of cycles and predictable workload. This leads to a high amount of different vehicle concepts ranging from large batteries, designed for a full day of operation without charging, to fast-charging systems with charging power up to a few hundred kilowatts. Hence, many different issues have to be addressed in the whole design and production process regarding high-voltage (HV) batteries for buses. In this work, the design process for electric public buses is analyzed in detail, based on two systems developed by the research projects Smart Wheels/econnect and SEB eÖPNV. The complete development process starting, with the demand analysis and the operating scenario, including the charging routine, is discussed. This paper also features details on cell selection and cost estimations as well as technical details on the system layout, such as the management system and passive components as well as thermal management.

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State of charge estimation for electric vehicle batteries using unscented kalman filtering

Cited by 305 publications

References 23 publications

Comparative Research on RC Equivalent Circuit Models for Lithium-Ion Batteries of Electric Vehicles

Comparative Research on RC Equivalent Circuit Models for Lithium-Ion Batteries of Electric Vehicles

Review of the Remaining Useful Life Prognostics of Vehicle Lithium-Ion Batteries Using Data-Driven Methodologies

Battery Design for Successful Electrification in Public Transport

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