Electric vehicle battery-ultracapacitor hybrid energy storage system and drivetrain optimization for a real-world urban driving scenario

Silva, Ludmila C. A.; Eckert, Jony Javorski; Lourenço, Maria Augusta de Menezes; Silva, Fabrício Lopes e; Corrêa, Fernanda Cristina; Dedini, Franco Giuseppe

doi:10.1007/s40430-021-02975-w

Cited by 29 publications

(8 citation statements)

References 65 publications

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“…Besides, the study determines the daily operating cost of the car by considering the battery and SC degradation model. Also, Silva et al 137 confirm the validity of Herrera et al by using the same technique to minimize the size of an HESS and improve the driving distance by optimizing the HESS power-sharing management for EVs. The study uses the parameters, including the urban driving cycle, vehicle drivetrain, HESS apparatuses, and their control, respectively, to assess the performance of the multi-objective GA.…”

Section: Optimization Techniquesmentioning

confidence: 75%

“…Dynamic programming 118,131,139,140 Provide near optimal control, 3-dimension possible 131 Offline use requires prior knowledge & no practical application 118 Electric vehicles 118,131 Wavelet-transform (Harr) 132,134 Offer effectiveness, simple, ordinary, less computational burden 134 -Plug-in hybrid electric vehicles 134 Fuzzy logic control 133,138 Effective, adaptive, intelligent, merge uncertainties & nonlinearities, incorporate heuristic control 133,138 Low computational efficiency, performance is sensitive to membership functions 133,138,150 SHE bus 138 Electric vehicles 133,150 Power splitting ratio 134 -Determined by the optimizer 134 PHEVs 134 Random forest + DP 140 Provide battery protection, enhance SC utilization, increase systems efficiency, reduce energy loss 140 -Electric vehicles 140 Genetic algorithm 135,137 Provide global optimum solution 135 There is no control tuning 132 -Electric vehicles 132 Light-railway vehicles 135 Pontryagin's minimum principle 144 Provide global optimal solutions, flexible, low computational burden, & Real-time control 144 -PHEVs 144 Convex programming 122 Rapidly & efficiently produce global optimum solutions 122 -Fuel cell/...…”

Section: Advantages Disadvantages Applicationsmentioning

confidence: 99%

“…Dynamic programming 118,130,131,139 It provides a globally optimal solution 139 Accurate 130 It requires prior knowledge & no real-time application 118 High computational cost 131 City buses 131 Electric vehicles 118 Renewable Energy 130 Convex programming 122 Computationally efficient & no "curse of dimensionality" 122 -Fuel cell hybrid electric vehicles 122 Dividing rectangle algorithm 117 Flexible & easily adaptable 117 No practical application Electric vehicles 117 Genetic algorithm 135,137,138,139,148 Provide a globally optimal solution 138 Ensure correct vehicle performance 135 -Series HEVs 138,139 Light-rail vehicles 135 Electric vehicles 137 Non-sorting genetic algorithm (NSGA-II) [132][133][134] Provide multiple Pareto-optimal solutions, no high computational complexity, no control parameter tuning 132 High computational complexity 140 Electric vehicles 132 Electric race car 133 PHEVs 134 Grey wolf optimization (GWO) 140,143 Trace non-convex problems, better convergence performance 143 -Electric vehicles 140 Traction substations 143 Pontryagin's minimum principle (PMP) 144 Flexible than DP, it provides a globally optimal solution, less computational effort, and possib...…”

Section: Sizing Technique Advantages Disadvantages Applicationsmentioning

confidence: 99%

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Hybrid energy storage system topology approaches for use in transport vehicles: A review

Lencwe

Chowdhury

Olwal

2022

Energy Science & Engineering

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High peak current for vehicle starting, recuperation of regenerative braking energy, longer battery lifespan, and more significant acceleration among others in modern transport vehicles (TVs) require increased battery size. Moreover, batteries have high energy density and low power density. Therefore, a big battery pack can weigh more, shorten its lifespan, increase vehicle total mass, and increase battery degradation costs. On the one hand, higher power energy storage systems (ESSs) such as supercapacitors, lithium-ion capacitors, and superconducting magnetic ESSs have a lower energy density, higher power density, and greater lifespan. Thus, to satisfy the requirements of modern TVs, the combination of higher energy and higher power density can provide enhanced performance and a longer battery lifespan for these vehicles. Available research publications in the literature have addressed a similar problem. However, these publications have reported the findings separately, providing various research and conclusions.Currently, no available literature has compiled an intelligible and combined analysis for addressing hybrid ESS configurations, sizing methods, and energy management strategies to create further knowledge in this domain. There is a need to consolidate a compact and insightful knowledge toward this research direction for a more significant societal and industrial impact. This paper critically reviews the hybrid higher energy density batteries and higher power density ESSs used in TVs. It discusses the integration configurations, applications, and provides sizing methods to achieve the best hybrid energy storage systems (HESSs). Also, applied control methods are described for these HESSs such that the overall system performance matches the vehicle requirements. Lastly, it provides insights and future research direction for HESS configuration, sizing, and control.

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Section: Optimization Techniquesmentioning

confidence: 75%

Section: Advantages Disadvantages Applicationsmentioning

confidence: 99%

Section: Sizing Technique Advantages Disadvantages Applicationsmentioning

confidence: 99%

See 1 more Smart Citation

Hybrid energy storage system topology approaches for use in transport vehicles: A review

Lencwe

Chowdhury

Olwal

2022

Energy Science & Engineering

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“…The several benefits of HESS over ESS including minimizing the stress, prolonging life cycle, and improving energy efficiency 13 . Lately, various combinations, such as FC‐BT, 14 FC‐SC, 15 SC‐BT, 16 FC‐SC‐BT 17 and BT‐FLW, 18 are evolved. The LIB‐SC‐based HESS (LIB‐SC HESS) received more attention because of prominent features: cost‐effective solution, mature technology, high power and energy densities, long life cycle, and low weight per unit capacity 19,20 …”

Section: Introductionmentioning

confidence: 99%

Lithium‐ionbattery and supercapacitor‐based hybrid energy storage system for electric vehicle applications: A review

Ahsan

Mekhilef

Soon

et al. 2022

Intl J of Energy Research

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Hybrid energy storage system (HESS) has emerged as the solution to achieve the desired performance of an electric vehicle (EV) by combining the appropriate features of different technologies. In recent years, lithium-ion battery (LIB) and a supercapacitor (SC)-based HESS (LIB-SC HESS) is gaining popularity owing to its prominent features. However, the implementation of optimal-sized HESS for EV applications is a challenging task due to the complex behavior of LIB and SC under different driving behaviors. Besides, the power electronics (PE) converter configurations and system-level optimizations, include component sizing (CS) and power-energy management strategy (PEMS), are essential for developing efficient HESS. Therefore, this paper reviews existing LIB-SC HESS, different possible combinations of CS and PEMS, generalized algorithm formulation, and algorithms used for both CS and PEMS. The current issues of LIB-SC HESS regarding the performance in EV applications, PE converters, and optimization algorithms are also analyzed. In addition, future recommendations for the development of efficient LIB-SC HESS are provided to inspire researchers for further studies. Highlights• Lithium-ion battery (LIB) and supercapacitor (SC)-based hybrid energy storage system (LIB-SC HESS) suitable for EV applications is analyzed comprehensively.

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“…A pesar de las suposiciones utilizadas, este planteo permite calcular un perfil de corriente apto para realizar ensayos preliminares. Para esto se emplean los lineamientos presentados en [182][183] [184], los cuales son directamente aplicados para transformar un perfil de velocidad de un VE en el perfil de potencia eléctrica requerida en el bus de continua del sistema. Para esto se parte de asumir movimiento rectilíneo uniforme para el VE, y calcular la sumatoria de fuerzas aplicadas como:…”

Section: Conversión De Potencia Mecánica Del Ve a Potencia Eléctricaunclassified

Desarrollo de metodologías de estimación para sistemas de almacenamiento de energía no convencionales en topologías híbridas

Fornaro¹

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Los sistemas de almacenamiento de energía son esenciales para alcanzar la sustentabilidad energética. Hoy día son un eslabón fundamental en el desarrollo de vehículos eléctricos, así como en la implementación a gran escala de los esquemas de generación eléctrica basados en energías renovables. Sin embargo, aún existen ciertas limitaciones tecnológicas, algunas de ellas intrínsecas al proceso de fabricación y otras dependientes del uso que se le da a estos sistemas. Teniendo este último aspecto en consideración, en esta tesis se presentan y desarrollan los principales avances en el área de la caracterización de módulos de almacenamiento de energía no convencionales (MANC). En particular, los esfuerzos se centran en el área de la estimación y observación para supercapacitores, baterías de Ión-Litio y baterías de flujo redox, aunque los desarrollos no se limitan a estos sistemas. Partiendo de un estudio exhaustivo de los modelos disponibles en la bibliografía, se realizan aportes en el área del modelado y se propone un esquema que permite observar los estados fundamentales de estos así como medidas validadas de los parámetros internos de los modelos adoptados. Los desarrollos de esta tesis se basan en la combinación de una multiplicidad de algoritmos, y el éxito de esta combinación requiere de un conocimiento detallado de cada uno de los métodos involucrados. Más precisamente, se emplean algoritmos de observación, estimación y control por modos deslizantes, algoritmos continuos y discretos de estimación. Por estos motivos, en primer lugar se realiza una presentación que condensa los aportes e ideas originales realizadas en las áreas de observación, estimación y modelado para MANC. Luego, en último lugar se presentan y analizan los principales resultados obtenidos.

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Electric vehicle battery-ultracapacitor hybrid energy storage system and drivetrain optimization for a real-world urban driving scenario

Cited by 29 publications

References 65 publications

Hybrid energy storage system topology approaches for use in transport vehicles: A review

Hybrid energy storage system topology approaches for use in transport vehicles: A review

Lithium‐ionbattery and supercapacitor‐based hybrid energy storage system for electric vehicle applications: A review

Desarrollo de metodologías de estimación para sistemas de almacenamiento de energía no convencionales en topologías híbridas

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