SoC Estimation for Lithium-ion Batteries: Review and Future Challenges

Barrera, Juan Pablo Rivera; Muñóz-Galeano, Nicolás; Maldonado, Henry

doi:10.3390/electronics6040102

Cited by 265 publications

(131 citation statements)

References 141 publications

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“…Moreover, NPC increased from $107,637 to $114,274. However, researchers have recommended that the SOC min not be set to an extremely low value to avoid damaging the storage bank by excessive discharge [62][63][64][65].…”

Section: Battery Minimum Socmentioning

confidence: 99%

Energy Management and Optimization of a PV/Diesel/Battery Hybrid Energy System Using a Combined Dispatch Strategy

et al. 2019

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In recent years, the concept of hybrid energy systems (HESs) is drawing more attention for electrification of isolated or energy-deficient areas. When optimally designed, HESs prove to be more reliable and economical than single energy source systems. This study examines the feasibility of a combined dispatch (CD) control strategy for a photovoltaic (PV)/diesel/battery HES by combining the load following (LF) strategy and cycle charging (CC) strategy. HOMER software is used as a tool for optimization analysis by investigating the techno-economic and environmental performance of the proposed system under the LF strategy, CC strategy, and combined dispatch CD strategy. The simulation results reveal that the CD strategy has a net present cost (NPC) and cost of energy (COE) values of $110,191 and $0.21/kWh, which are 20.6% and 4.8% lower than those of systems utilizing the LF and CC strategies, respectively. From an environmental point of view, the CD strategy also offers the best performance, with CO 2 emissions of 27,678 kg/year. Moreover, the results show that variations in critical parameters, such as battery minimum state of charge, time step, solar radiation, diesel price, and load growth, exert considerable effects on the performance of the proposed system. Sustainability 2019, 11, 683 2 of 26 different energy sources to produce a hybrid energy system (HES), which can solve reliability problems and provide an environmentally friendly solution [7][8][9]. Various power sources and storages, such as diesel generators, batteries, and supercapacitors, should be integrated into HESs to improve system stability and smooth out fluctuations [10,11].Sustainability 2018, 10, x FOR PEER REVIEW 2 of 29 problems and provide an environmentally friendly solution [7][8][9]. Various power sources and storages, such as diesel generators, batteries, and supercapacitors, should be integrated into HESs to improve system stability and smooth out fluctuations [10,11]. Figure 2. Commonly used approaches for energy management strategies [14]. Sustainability 2019, 11, 683 3 of 26Although the non-dispatchable RESs necessitate complex systems modeling, they are themselves simple to model without the need for control logic, in which the power is merely produced in direct response to the available renewable energy resources. On the other hand, the dispatchable components, such as the generator and battery, are more difficult to model because they must be controlled to achieve matching of demand and supply properly, and to compensate for the intermittency of the non-dispatchable RESs [16,17]. "Should a generator charge the battery or should excess solar production be responsible for charging the battery only and the generator used only to satisfy the load?" This question has led to some rules that manage the operation of generator and battery energy storage. The load following (LF) and cycle charging (CC) dispatch strategies are used to control generator operation and battery energy storage. Under the LF strategy, a generator produces only e...

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Section: Battery Minimum Socmentioning

confidence: 99%

Energy Management and Optimization of a PV/Diesel/Battery Hybrid Energy System Using a Combined Dispatch Strategy

et al. 2019

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“…During the test runs of the IPEMU train for instance, the state of charge below 25% was not observed. The method used in this paper to measure the state of charge is based on the Coulomb counting method, which measures the state of charge according to the integral of the current [52]. This method, although accurate, is sensitive to the initial value of the state of charge.…”

Section: Battery Models Validationmentioning

confidence: 99%

Speed profile optimization of catenary-free electric trains with lithium-ion batteries

et al. 2019

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Catenary-free operated electric trains, as one of the recent technologies in railway transportation, has opened a new field of research: speed profile optimization and energy optimal operation of catenary-free operated electric trains. A well-formulated solution for this problem should consider the characteristics of the energy storage device using validated models and methods. This paper discusses the consideration of the lithium-ion battery behavior in the problem of speed profile optimization of catenary-free operated electric trains. We combine the single mass point train model with an electrical battery model and apply a dynamic programming approach to minimize the charge taken from the battery during the catenary-free operation. The models and the method are validated and evaluated against experimental data gathered from the test runs of an actual battery-driven train tested in Essex, UK. The results show a significant potential in energy saving. Moreover, we show that the optimum speed profiles generated using our approach consume less charge from the battery compared to the previous approaches.

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“…Calculate the Jacobian matrix using Equation (34) with: d. Update the parameters using Equation (33) and Equations (7)- (10). e.…”

Section: L-m Algorithmmentioning

confidence: 99%

A Novel Intelligent Method for the State of Charge Estimation of Lithium-Ion Batteries Using a Discrete Wavelet Transform-Based Wavelet Neural Network

et al. 2018

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State of charge (SOC) estimation is becoming increasingly important, along with electric vehicle (EV) rapid development, while SOC is one of the most significant parameters for the battery management system, indicating remaining energy and ensuring the safety and reliability of EV. In this paper, a hybrid wavelet neural network (WNN) model combining the discrete wavelet transform (DWT) method and adaptive WNN is proposed to estimate the SOC of lithium-ion batteries. The WNN model is trained by Levenberg-Marquardt (L-M) algorithm, whose inputs are processed by discrete wavelet decomposition and reconstitution. Compared with back-propagation neural network (BPNN), L-M based BPNN (LMBPNN), L-M based WNN (LMWNN), DWT with L-M based BPNN (DWTLMBPNN) and extend Kalman filter (EKF), the proposed intelligent SOC estimation method is validated and proved to be effective. Under the New European Driving Cycle (NEDC), the mean absolute error and maximum error can be reduced to 0.59% and 3.13%, respectively. The characteristics of high accuracy and strong robustness of the proposed method are verified by comparison study and robustness evaluation results (e.g., measurement noise test and untrained driving cycle test).

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SoC Estimation for Lithium-ion Batteries: Review and Future Challenges

Cited by 265 publications

References 141 publications

Energy Management and Optimization of a PV/Diesel/Battery Hybrid Energy System Using a Combined Dispatch Strategy

Energy Management and Optimization of a PV/Diesel/Battery Hybrid Energy System Using a Combined Dispatch Strategy

Speed profile optimization of catenary-free electric trains with lithium-ion batteries

A Novel Intelligent Method for the State of Charge Estimation of Lithium-Ion Batteries Using a Discrete Wavelet Transform-Based Wavelet Neural Network

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