Design and validation of a battery management system for solar-assisted electric vehicles

Wei, Hongqian; Zhang, Yan; Fan, Likang; Ai, Qiang; Zhao, Wenqiang; Jing, Rui; Zhang, Youtong

doi:10.1016/j.jpowsour.2021.230531

Cited by 14 publications

(6 citation statements)

References 36 publications

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“…In the model, U ocv and U t represent the open-circuit voltage and the terminal voltage of the circuit, respectively, where I correspond to the current flowing through the circuit. CPE represents fractional-order capacitance and its definition of fractional capacitance in the frequency domain is shown in Equation (1).…”

Section: Second-order Fractional Order Equivalent Circuit Modelmentioning

confidence: 99%

“…In recent years, lithium-ion batteries have been greatly developed and widely used as a power source for electric vehicles (EVs) under the concept of sustainable development due to the advantages of high storage capacity, long life, and high output power. [1,2] The battery state of charge (SOC) is one of the core indicators in the battery management system (BMS). [3,4] It can not only provide the remaining power battery charge for the driver to judge the vehicle range, but it can also effectively prevent the battery from being overcharged or overdischarged, thereby protecting the battery and extending its life.…”

Section: Introductionmentioning

confidence: 99%

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Improved Backward Smoothing Square Root Cubature Kalman Filtering and Fractional Order—Battery Equivalent Modeling for Adaptive State of Charge Estimation of Lithium‐Ion Batteries in Electric Vehicles

Zhou,

Wang,

Cao

et al. 2023

Energy Tech

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The accuracy of lithium‐ion battery state of charge (SOC) estimation affects the driving distance, battery life, and safety performance of electric vehicles. Herein, the polarization reaction inside the battery is modeled using a second‐order fractional‐order equivalent circuit model and uses an adaptive genetic algorithm for model parameter identification. Then, an improved adaptive fractional‐order backward smoothing square root cubature Kalman filtering algorithm (AFOBS‐SRCKF) is proposed by integrating Sage Husa adaptive filtering and backward smoothing processes to optimize the square root cubature Kalman filter for improving the accuracy and adaptability of real‐time estimation of SOC in a complex environment. Finally, the algorithm is compared with the integer‐order SRCKF, fractional‐order SRCKF through simulation, and fractional‐order backward smoothing SRCKF through simulation. Under complex operating conditions, the error sum of SOC estimation of the AFOBS‐SRCKF algorithm is controlled within 1.0% and the convergence speed is improved by at least 30%. The results show that the AFOBS‐SRCKF algorithm effectively improves the accuracy, stability, and convergence of SOC estimation.

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Section: Second-order Fractional Order Equivalent Circuit Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improved Backward Smoothing Square Root Cubature Kalman Filtering and Fractional Order—Battery Equivalent Modeling for Adaptive State of Charge Estimation of Lithium‐Ion Batteries in Electric Vehicles

Zhou,

Wang,

Cao

et al. 2023

Energy Tech

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“…A large number of researches have been done for the improvement of PV system efficiency, different approaches are employed for the tracking of maximum power point from PV module for solving the efficiency problems and many products with these procedures are available in market for consumers [10], [11]. Solar power is the most efficient and practical alternative source of renewable energy [12], [13]. The SPEVs are far away from physical world feasibility because of their cost, energy shortcomings, and low power density [14].…”

Section: Introductionmentioning

confidence: 99%

Modeling and analysis of solar-powered electric vehicles

Nivas

Naidu

Mishra

et al. 2022

IJPEDS

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The emission of greenhouse gasses from transportation vehicles is one of the most alarming environmental threats and the emission of these gases is mounting at a distressing pace. Limited fossil fuel resources are also a threat to the automobile industry. This work aims to describe the solar-powered electric vehicle (SPEV) as the key to solving the downside of fuel and pollution. A battery is used in an electric vehicle (EV) which is charged from both external power supply and also from photovoltaic (PV) panels which absorb radiation from the sunlight and generate electrical power. A maximum power point tracker (MPPT) controller is employed to track the utmost power. A buck-Boost converter is utilized to amplify the DC voltage procured from the photovoltaic module and then the boosted output is transmitted to a three-phase voltage source inverter (VSI). VSI is used to transform the solar DC voltage to AC voltage and feeds the brushless direct current (BLDC) motor which controls vehicle applications.

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“…The performance of the battery depends on the efficiency of the battery management system (BMS). [5][6][7][8] The main function of the BMS is to monitor the operating status of the battery in complex environments. It includes several aspects such as battery state of charge (SOC), state of health (SOH), battery thermal management, and safety management.…”

mentioning

confidence: 99%

Battery State of Health Model Estimation Based on Variable Projection Algorithm Using Steffensen Acceleration Method

Cheng

Chen

et al. 2023

J. Electrochem. Soc.

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The variable projection based Steffensen acceleration (VP-SA) algorithm is proposed for battery state of health estimation. The VP-SA algorithm exploits the separability of variables to reduce the dimensionality of the parameters, which can improve the estimation efficiency. In addition, based on the Steffensen acceleration method, the convergence rates of the VP algorithm can be increased. The simulation example shows the effectiveness of the proposed algorithm.

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Design and validation of a battery management system for solar-assisted electric vehicles

Cited by 14 publications

References 36 publications

Improved Backward Smoothing Square Root Cubature Kalman Filtering and Fractional Order—Battery Equivalent Modeling for Adaptive State of Charge Estimation of Lithium‐Ion Batteries in Electric Vehicles

Improved Backward Smoothing Square Root Cubature Kalman Filtering and Fractional Order—Battery Equivalent Modeling for Adaptive State of Charge Estimation of Lithium‐Ion Batteries in Electric Vehicles

Modeling and analysis of solar-powered electric vehicles

Battery State of Health Model Estimation Based on Variable Projection Algorithm Using Steffensen Acceleration Method

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