Optimal fuzzy logic based energy management strategy of battery/supercapacitor hybrid energy storage system for electric vehicles

Gao, Chao; Zhao, Jian; Wu, Jian; Hao, Xiongbo

doi:10.1109/wcica.2016.7578246

Cited by 11 publications

(9 citation statements)

References 1 publication

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“…Usually, most FLC is used as a joint control strategy to combine with other EMS to improve the optimal operating conditions and to adapt different driving behaviors of EV. Gao et al 117 improved the traditional FLC by implementing optimization results for a pure EV utilizing battery -SC hybrid system. At the same time, Dusmez et al 118 modified the similar EV with wavelet transform (WT) and improved the adaptivity of the control system.…”

Section: Fuzzy Logic-based Energy Management Strategymentioning

confidence: 99%

A review on hybrid source energy management strategies for electric vehicle

Kashyap

Castelino

2021

Int J Energy Res

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Electric and hybrid electric vehicle technology demonstrates a performance to replace the internal combustion engines (ICE) in the current scenario. It attracts attention with improved fuel or energy efficiency with lower emissions. The overall system performance depends on powertrains, types of energy sources, electro-electronic interfaces, and energy management strategies (EMS). Significant issues of battery-powered electric vehicles (EV) are effects on the range, battery life, EV performance, battery maintenance, and replacement cost. Hybrid power source system (HPSS) solves EV challenges to a large extent. A hybrid combination of battery and supercapacitor (SC) to power the EV enhances the overall performance and life of the vehicle. Learning and integrated-based EMSs are gaining attention, with their ability in accurate and fast response in power handling among various sources. This paper analyses various DC-DC converter topologies of HPSS and compares multiple EMS with recent developments. In the context of challenges involved in EVs and research gaps that are discussed in the paper, EMSs need to be enhanced. The EMSs must consider the inputs for varying driving behaviors, road traffic, load, and environmental conditions to assure the flexibility of EV among different users across the globe. This is achieved by the management of SC power available to support the vehicle during sudden power requirements and enabling it to recuperate braking energy to improve the energy efficiency throughout the trip. Lastly, recommending precise research directions to achieve the development and improvement of the EMS and power electronic interfaces. K E Y W O R D Sbattery, electric vehicle (EV), energy management strategies (EMSs), hybrid power source systems (HPSS), supercapacitor (SC)

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Section: Fuzzy Logic-based Energy Management Strategymentioning

confidence: 99%

A review on hybrid source energy management strategies for electric vehicle

Kashyap

Castelino

2021

Int J Energy Res

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“…The rule-based strategy just takes system energy states and momentary instantaneous power demand into consideration, and the power distribution mission is usually achieved according to a series of predefined rules [10]. Representative examples include threshold [11,12], fuzzy logic [13,14] and filtration [15,16]. A rule-based controller is proposed based on considering the power demand of the load and the states of charge (SOC) of batteries and supercapacitors at the same time [11].…”

Section: Introductionmentioning

confidence: 99%

“…A rule-based controller is proposed based on considering the power demand of the load and the states of charge (SOC) of batteries and supercapacitors at the same time [11]. In [13], the author adopted a golden cut-off rule to optimize a fuzzy logic controller, and simulation results indicate that the designed controller could effectively achieve the goals they set. In [15], a controller adopted a low-pass filter to separate the load power into high frequency and low frequency, then distributed them to the SC and battery.…”

Section: Introductionmentioning

confidence: 99%

Energy Management Strategy of Hybrid Energy Storage System Based on Road Slope Information

Zhi³

et al. 2021

Energies

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To maximize the performance of power batteries and supercapacitors in a hybrid energy storage system (HESS) and to resolve the conflict between the high power demands of electric vehicles and the limitations of high-current charging and discharging of the power battery, a vehicle power demand model incorporating road slope information has been constructed. This paper takes a HESS composed of power battery and supercapacitor as the object, and a rule-based energy management strategy (EMS) based on road slope information is proposed to realize the reasonable distribution and management of energy under the slope condition. According to the slope information of the road ahead, the energy consumption in the next period was predicted, and the supercapacitor is charged and discharged in advance to meet the energy demand of uphill and the energy recovery capacity of downhill to avoid the high current charge and discharge of the battery. Subsequently, the improved EMS performance was simulated under the New York City Cycle (NYCC) driving conditions with additional slope driving conditions. The simulated results indicate that compared to the existing EMS, the proposed EMS based on slope information can effectively distribute the power demand between the power battery and the supercapacitor, can reduce the discharge current and the duration of high-power discharge, and has a 20.4% higher energy recovery efficiency, effectively increasing the cruising range.

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“…To reduce parameter-design difficulty and enable better control performance, many researchers considered combining other algorithms with FIS such as wavelet-fuzzy strategies [25][26][27]. Another deficiency concerning current research on FIS-based energy management is that simulation models are often simplified for fast simulations, with reduced accuracy [28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Traffic-Condition-Prediction-Based HMA-FIS Energy-Management Strategy for Fuel-Cell Electric Vehicles

Yao

et al. 2019

Energies

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In the field of Fuel Cell Electric Vehicles (FCEVs), a fuel-cell stack usually works together with a battery to improve powertrain performance. In this hybrid-power system, an Energy Management Strategy (EMS) is essential to configure the hybrid-power sources to provide sufficient energy for driving the FCEV in different traffic conditions. The EMS determines the overall performance of the power supply system; accordingly, EMS research has important theoretical significance and application values on the improvement of energy-utilization efficiency and the serviceability of vehicles' hybrid-power sources. To overcome the deficiency of apparent filtering lag and improve the adaptability of an EMS to different traffic conditions, this paper proposes a novel EMS based on traffic-condition predictions, frequency decoupling and a Fuzzy Inference System (FIS). An Artificial Neural Network (ANN) was designed to predict traffic conditions according to the vehicle's running parameters; then, a Hull Moving Average (HMA) algorithm, with filter-window width decided by the prediction result, is introduced to split the demanded power and keep low-frequency components in order to meet the load characteristics of the fuel cell; afterward, an FIS was applied to manage power flows of the FCEV's hybrid-power sources and maintain the State of Change (SoC) of the battery in a predefined range. Finally, an FCEV simulation platform was built with MATLAB/Simulink and comparison simulations were carried out with the standard test cycle of the Worldwide harmonized Light vehicle Test Procedures (WLTPs). Simulation results showed that the proposed EMS could efficiently coordinate the hybrid-power sources and support the FCEV in following the reference speed with negligible control errors and sufficient power supply; the SoC of the battery was also maintained with good adaptability in different driving conditions.

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Optimal fuzzy logic based energy management strategy of battery/supercapacitor hybrid energy storage system for electric vehicles

Cited by 11 publications

References 1 publication

A review on hybrid source energy management strategies for electric vehicle

A review on hybrid source energy management strategies for electric vehicle

Energy Management Strategy of Hybrid Energy Storage System Based on Road Slope Information

Traffic-Condition-Prediction-Based HMA-FIS Energy-Management Strategy for Fuel-Cell Electric Vehicles

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