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State of charge

About: State of charge is a research topic. Over the lifetime, 12013 publications have been published within this topic receiving 201419 citations. The topic is also known as: SoC & SOC.


Papers
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Journal ArticleDOI
13 May 2016
TL;DR: In this paper, an electric battery model utilizing multiple time constants, to address ranges of seconds, minutes, and hours, is developed, with model parameters including open-circuit voltage, series resistance, and equivalent RC circuits, with nonlinear dependence on battery SOC.
Abstract: Simulation of electric vehicles (EVs) over driving schedules within a fully dynamic EV simulator requires battery models capable of accurately and quickly predicting state of charge (SOC), $I$ – $V$ characteristics, and dynamic behavior of various battery types. An electric battery model utilizing multiple time constants, to address ranges of seconds, minutes, and hours, is developed. The model parameters include open-circuit voltage, series resistance, and equivalent RC circuits, with nonlinear dependence on battery SOC. The SOC captures effects from discharge and charge rate, temperature, and battery cycling. Thermal modeling predicting real-time battery temperature is introduced. One focus of this paper is presenting a systematic and generic methodology for parameter extraction as well as obtaining SOC factors through reasonable test work when evaluating any given lithium-ion (Li-ion), nickel-metal hydride, or lead-acid battery cell. In particular, data sets for a Panasonic CGR18650 Li-ion battery cell are tabulated for direct use. The Li-ion battery model is programmed into a MATLAB/Simulink environment and used as a power source within an existing comprehensive dynamic vehicle simulator. Validation of the Simulink model is through a battery testing apparatus with a hardware-in-the-loop driving schedule that cycles real batteries. Results from simulations and measurements of Li-ion battery packs show that the proposed battery model behaves well and interacts appropriately with other subcomponents of the vehicle simulator.

99 citations

Journal ArticleDOI
TL;DR: In this article, the authors quantitatively analyzes the energy losses that take place during the charging of a battery electric vehicle (BEV), focusing especially in the previously unexplored 80% -100% State of Charge (SoC) area.

98 citations

Journal ArticleDOI
TL;DR: The result shows that MOPSO yields positive performance and the proposed system is recommended as the best substitute to improve electric energy utilization in remote areas.

98 citations

Journal ArticleDOI
TL;DR: A model-based diagnostic scheme is presented that uses sliding mode observers designed based on the electrical and thermal dynamics of the battery to enable the detection, the isolation, as well as the estimation of the temperature, voltage, and current sensor faults.
Abstract: In battery management systems (BMSs), real-time diagnosis of sensor faults is critical for ensuring the safety and reliability of the battery. For example, a current sensor fault leads to erroneous estimates of state of charge and other parameters, which in turn affects the control actions in the BMS. A temperature sensor fault may lead to ineffective thermal management. In this brief, a model-based diagnostic scheme is presented that uses sliding mode observers designed based on the electrical and thermal dynamics of the battery. It is analytically shown how the extraction of the equivalent output error injection signals on the sliding manifolds enables the detection, the isolation, as well as the estimation of the temperature, voltage, and current sensor faults. This brief includes simulation and experimental studies to demonstrate and evaluate the effectiveness of the proposed scheme. Discussions are also included on the effects of uncertainty and on threshold design.

98 citations

Journal ArticleDOI
TL;DR: In this paper, an application of Equivalent Consumption Minimization Strategy (ECMS) for PHEV is presented and benchmarked against the dynamic programming (DP) for information requirement and optimality.
Abstract: One strategy to minimise petroleum fuel consumption of a Plug-in Hybrid Electric Vehicle (PHEV) is to attain the lowest admissible battery State of Charge (SOC) at the end of driving cycle while following an optimal SOC profile. The challenge of an optimisation algorithm is to find this optimal profile by using least future information about the power demand. An application of Equivalent Consumption Minimisation Strategy (ECMS) for PHEV is presented in this paper and benchmarked against the dynamic programming (DP) for information requirement and optimality. The optimality is assessed in simulation by considering petroleum fuel economy and deviation of the optimal SOC profile from a reference profile for different driving scenarios and battery sizes. Results show that for longer distances and larger battery sizes, ECMS and DP provide similar fuel economy and SOC profiles. A sensitivity analysis with respect to driving distance is presented at the end of the paper.

98 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023692
20221,326
2021926
20201,245
20191,285
20181,147