A New Ultracapacitor State of Charge Control Concept to Enhance Battery Lifespan of Dual Storage Electric Vehicles

Alobeidli, Khaled; Khadkikar, Vinod

doi:10.1109/tvt.2018.2871038

Cited by 40 publications

(27 citation statements)

References 30 publications

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“…A Toyota Rav4EV model was tested and showed improved response of NMPC compared to LMPC. Different control was applied in HESS for EV in [34]. A two-stage neural network was used to control the SOC of the supercapacitor.…”

Section: Figure 1 Common Hess Architectures [11]mentioning

confidence: 99%

Optimal Control Strategy to Maximize the Performance of Hybrid Energy Storage System for Electric Vehicle Considering Topography Information

et al. 2020

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This research designed an energy management system involving a battery-supercapacitor Hybrid Energy Storage System (HESS) for electric vehicles (EV). The objective is to improve the performance of the HESS by combining battery and supercapacitor features, accounting for topographical information to guarantee continuous hybridization during the drive cycle. Contour Positioning System (CPS) was used to determine the slope of the rode travelled by the vehicle. Two adaptive algorithms were designed for a rule-based controller to control the energy shared between the battery and the supercapacitor; an optimal adaptive controller and fuzzy adaptive controller. The HESS model, electric vehicle and controllers were tested using MATLAB/Simulink with three real drive cycles, namely, uphill, downhill and city tour, in three different speeds 50Km/h, 60Km/h and 70 Km/h. The results proved the controllers managed to extend battery life-cycle by reducing the stress on the battery for the drive cycles. The results were compared in terms of energy consumption for the optimal adaptive rule-based controller and fuzzy adaptive rule-based controller. The optimal adaptive rule-based controller guaranteed the HESS was able to operate continuously and extend the number of drive cycles in a wide range of speeds and road slopes. INDEX TERMS Electric vehicles; Energy storage; Energy management; Navigation.

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Section: Figure 1 Common Hess Architectures [11]mentioning

confidence: 99%

Optimal Control Strategy to Maximize the Performance of Hybrid Energy Storage System for Electric Vehicle Considering Topography Information

et al. 2020

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“…I dc_link is the DC-link current and its expression is 0, ±I A , ±I B , and ±I C based on the states of S 1 -S 6 [21]. Combining Equations (6), (8), and (10), the ST current and the current stress in S 1 -S 7 can be alleviated through the power provided by the energy storage unit. This indicates that the device loss can be reduced and the energy transfer efficiency can be improved through power distribution in the ES-qZSI.…”

Section: Device Stress Analysis For Es-qzsimentioning

confidence: 99%

“…The derivation is demonstrated in Appendix A and the result is shown in Table 1. Due to the combination of the ST current and the phase current in the devices S 1 -S 7 , as in Equations (8) and 10, the zero-crossing point of device current and the commutation duration of the diode change. Its effect on the device power losses is represented by the coefficients α 1 -α 6 in Table 1.…”

Section: Power Loss Profile Derivation For Es-qzsimentioning

confidence: 99%

“…Inductor loss (1) As shown in Equations (8) and (9), the coefficient of IST is smaller compared with that of Iph. Therefore, the AC side device switching loss Psw-ac and conduction loss Pcon-ac are mainly dominated by Iph and are relatively insensitive to IST, as shown in Figure 3.…”

Section: Item Expression Coefficientmentioning

confidence: 99%

“…Improving efficiency through power distribution regulation was proposed [6]. These power distribution methods were also applied for applications such as electric vehicles and elevators [7][8][9]. MEET has proved to be effective for power conversion system (PCS) applications in AC or DC micro-grids.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Energy Efficiency Tracking in the Energy-Stored Quasi-Z-Source Inverter

Liang

Zhou

et al. 2020

Energies

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In this paper, the interaction between the energy storage (ES) power distribution and system efficiency enhancement is researched based on the energy stored quasi-Z-source inverter. The corresponding current counteraction, stress reduction, power loss profile, and efficiency enhancement around the embedded energy storage units are studied in details. Firstly, the current counteraction effect on the device current is presented with the embedded ES source. The corresponding reduction in the device current stress is revealed. Then, the detailed device power loss expressions with current redistribution in the impedance network are explored mathematically. A quasi-inverted-trapezoidal power loss profile is found with the embedded source power distribution. To further increase the overall system efficiency, an optimal energy efficiency tracking strategy is proposed for the ES-qZSI (energy-stored quasi-Z-source inverter) based on the power distribution control. Both the simulation and the experiment verified that the power loss is reduced by over 40% through the proposed efficiency enhancement method. The device current and loss analysis for the embedding of energy storage can also be extended to the operating range optimization in other ES systems.

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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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A New Ultracapacitor State of Charge Control Concept to Enhance Battery Lifespan of Dual Storage Electric Vehicles

Cited by 40 publications

References 30 publications

Optimal Control Strategy to Maximize the Performance of Hybrid Energy Storage System for Electric Vehicle Considering Topography Information

Optimal Control Strategy to Maximize the Performance of Hybrid Energy Storage System for Electric Vehicle Considering Topography Information

Optimal Energy Efficiency Tracking in the Energy-Stored Quasi-Z-Source Inverter

A review on hybrid source energy management strategies for electric vehicle

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