Distance‐oriented hierarchical control and ecological driving strategy for HEVs

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163948/1/els2bf00154.pd

Routing Optimization of Electric Vehicles for Charging With Event-Driven Pricing Strategy

With the increasing market penetration of electric vehicles (EVs), the charging behavior and driving characteristics of EVs have an increasing impact on the operation of power grids and traffic networks. Existing research on EV routing planning and charging navigation strategies mainly focuses on vehicle-road-network interactions, but the vehicle-to-vehicle interaction has rarely been considered, particularly in studying simultaneous charging requests. To investigate the interaction of multiple vehicles in routing planning and charging, a routing optimization of EVs for charging with an event-driven pricing strategy is proposed. The urban area of a city is taken as a case for numerical simulation, which demonstrates that the proposed strategy can not only alleviate the long-time queuing for EV fast charging but also improve the utilization rate of charging infrastructures. Note to Practitioners - This article was inspired by the concerns of difficulties for electric vehicle (EV)'s fast charging and the imbalance of the utilization rate of charging facilities. Existing route optimization and charging navigation research are mainly applicable to static traffic networks, which cannot dynamically adjust driving routes and charging strategies with real-time traffic information. Besides, the mutual impact between vehicles is rarely considered in these works in routing planning. To resolve the shortcomings of existing models, a receding-horizon-based strategy that can be applied to dynamic traffic networks is proposed. In this article, various factors that the user is concerned about within the course of driving are converted into driving costs, through which each road section of traffic networks is assigned the corresponding values. Combined with the graph theory analysis method, the mathematical form of the dynamic traffic network is presented. Then, the article carefully plans and adjusts EV driving routes and charging strategies. Numerical results demonstrate that the proposed method can significantly increase the adoption of EV fast charging while alleviating unreasonable distributions of regional charging demand.</p

Energy Management Improvement of Hybrid Electric Vehicles via Combined GPS/Rule-Based Methodology

International audienceThis paper aims at proposing an efficient and versatile application of Petri nets (PNs) either alone without global positioning system (GPS) as in (GPS-free) system or together with the navigation system (GPS-registered) to conveniently provide a proper energy management strategy for hybrid electric vehicles (HEVs) of high hybridization level and serial architecture. A comparison between the PN strategy and two fuzzy logic strategies is performed in terms of fuel consumption and convergence time. In this paper, short and long trip types of 30 km mainly urban and 240 km mostly highway are considered with an initial state of charge (SoC) of 50% and different daily driving cycles or various standard the New York City Cycle, the New European Driving Cycle, US06 driving cycles. Both kinds of battery management strategies, GPS-free and GPS registered, are demonstrated and compared through simulation studies using the MTCsim software. Dealing with both types of trips, the simulation results significantly illustrate the superiority of the novel GPS-registered methodology's efficiency toward improving the HEV's energy management and reducing its fuel consumption besides the relative economic feasibility and structural simplicity features. Over one week duration, the GPS allows reaching the desired final SoC with acceptable errors and reducing the fuel consumption for both daily short and weekend long trips. The originality of this paper is proposing a hybrid GPS/rule-based approach to reduce the fuel consumption during daily driving trips that present about half of the professional travels in 2008 according to the French Sustainable Development Division. This novel strategy is developed on the basis of the recorded GPS data from past trips and the batteries' final recharging capacities

Optimized Energy Management Schemes for Electric Vehicle Applications: A Bibliometric Analysis towards Future Trends

Concerns over growing greenhouse gas (GHG) emissions and fuel prices have prompted researchers to look into alternative energy sources, notably in the transportation sector, accounting for more than 70% of carbon emissions. An increasing amount of research on electric vehicles (EVs) and their energy management schemes (EMSs) has been undertaken extensively in recent years to address these concerns. This article aims to offer a bibliometric analysis and investigation of optimized EMSs for EV applications. Hundreds (100) of the most relevant and highly influential manuscripts on EMSs for EV applications are explored and examined utilizing the Scopus database under predetermined parameters to identify the most impacting articles in this specific field of research. This bibliometric analysis provides a survey on EMSs related to EV applications focusing on the different battery storages, models, algorithms, frameworks, optimizations, converters, controllers, and power transmission systems. According to the findings, more articles were published in 2020, with a total of 22, as compared to other years. The authors with the highest number of manuscripts come from four nations, including China, the United States, France, and the United Kingdom, and five research institutions, with these nations and institutions accounting for the publication of 72 papers. According to the comprehensive review, the current technologies are more or less capable of performing effectively; nevertheless, dependability and intelligent systems are still lacking. Therefore, this study highlights the existing difficulties and challenges related to EMSs for EV applications and some brief ideas, discussions, and potential suggestions for future research. This bibliometric research could be helpful to EV engineers and to automobile industries in terms of the development of cost-effective, longer-lasting, hydrogen-compatible electrical interfaces and well-performing EMSs for sustainable EV operations

Towards sustainable urban living: A holistic energy strategy for electric vehicle and heat pump adoption in residential communities

Electric vehicles (EVs) and heat pumps (HPs) are key in reducing carbon emissions from transportation and domestic heating, yet their adoption may increase peak load demands on electrical networks. One of the aims of this research is to assess the potential impact of uncontrolled EV charging on community-scale distribution networks, exploring how this could stress the existing electrical infrastructure. It also explores the role of EVs in Vehicle-to-Grid (V2G) and smart charging applications, aiming to enhance community distribution systems. The study investigates the maximum stabilisation level achievable under various scenarios, highlighting the importance of smart energy management in integrating renewable energy and addressing uncertainties in the modelling process. Additionally, this study discusses the proposed systems' scalability, consumer behaviours' impact on the suggested energy solutions, and the potential implications of recent technological advancements for simulated communities. The research employs a sophisticated, integrative approach, combining stochastic methods with several robust energy software. Key findings suggest that uncontrolled EV charging can lead to grid capacity issues at high EV penetration levels, particularly during colder months. While smart charging and V2G technologies can moderate peak loads in many scenarios, achieving 100% sustainable technology integration requires enhanced energy management or increased network capacity, especially in winter. Wind and solar power integration demonstrates strategic complementarity, particularly in winter, enhancing the reliability and stability of the community grid. It is also observed that peak solar generation hours misalign with the community's highest demand times, posing challenges for solar energy utilisation in EV charging in residential-based area

Aportaciones al dimensionamiento y gestión de energía de un tren de potencia eléctrico híbrido para vehículos industriales con ciclos de conducción repetitivos y agresivos

Currently, the interest for helping mitigate the emission of greenhouse gases caused by high fuel consumption in industrial vehicles has increased. In order to the reduction of fuel consumption in an industrial vehicle, it has been proposed to incorporate into the powertrain a system capable of storing and supplying electrical energy. Consequently, the design of a hybrid electric powertrain is required, based on the interconnection of the elements (topology), the sizing of the elements and/or the energy management strategy of the powertrain. This paper presents a methodology for the design of a hybrid electric vehicle for refuse collection, which presents a repetitive and aggressive drive cycle as a result of work activity. The proposed methodology consists in modeling the behavior of a hybrid electric powertrain, considering the electrical behavior of various energy accumulation elements (batteries and supercapacitors). An embedded system is used to perform the experimental characterization of a cell and a commercial supercapacitor, in order to approximate the behavior through an electric model. In accordance with a real drive cycle of a refuse collection vehicle, the energy demand for a hybrid electric refuse collection vehicle is determined. On the other hand, the fuel consumption is calculated from a hybrid electric powertrain that integrates an energy storage system or a hybrid energy storage system. A bio-inspired metaheuristic based on a stochastic population (particle swarm optimization and genetic algorithm) is developed, in order to determine an optimal solutions space. Subsequently, the optimal sizing of an energy storage system (batteries) and a hybrid energy storage system (batteries and supercapacitors) is performed, considering different mono-objective and multi-objective optimization problems. Based on the results of each optimization problem, a comparative analysis is carried out with an element of commercial accumulation. Considering a hybrid electric powertrain that integrates a hybrid energy storage system (batteries and supercapacitors), an energy management strategy based on fuzzy logic is developed. This includes the identification of the vehicle status from a real drive cycle. Finally, the validation of the energy management strategy is carried out through the model of a hybrid electric vehicle for refuse collection.Actualmente, se ha incrementado el interés por mitigar la emisión de gases de efecto invernadero que se produce por un elevado consumo de combustible en vehículos industriales. Con la intención de contribuir en la reducción del consumo de combustible de un vehículo industrial, se ha propuesto incorporar al tren de potencia un sistema capaz de almacenar y suministrar energía eléctrica. En consecuencia, surge la necesidad de realizar el diseño de un tren de potencia eléctrico híbrido, a partir de la interconexión de los elementos (topología), el dimensionamiento de los elementos y/o la estrategia de gestión de energía del tren de potencia. En el presente trabajo se presenta una metodología para realizar el diseño de un vehículo eléctrico híbrido de recolección de basura, que presenta un ciclo de conducción repetitivo y agresivo como resultado de la actividad laboral. La metodología propuesta consiste en modelar el comportamiento de un tren de potencia eléctrico híbrido, considerando el comportamiento eléctrico de diversos elementos de acumulación de energía híbrido (baterías y supercapacitores). Se emplea un sistema embebido para realizar la caracterización experimental de una celda y un supercapacitor comercial, con el propósito de aproximar el comportamiento a través de un modelo eléctrico. En función de un ciclo de conducción real de un vehículo de recolección de basura se determina la demanda de energía para un vehículo eléctrico híbrido de recolección de basura. Por otra parte, se calcula el consumo de combustible a partir de un tren de potencia eléctrico híbrido que integra un sistema de almacenamiento de energía o un sistema de almacenamiento de energía híbrido. Se desarrolla una metaheurística bio-inspirada basada en una población estocástica) para determinar un espacio de soluciones óptimas. Posteriormente, se realiza el dimensionamiento óptimo de un sistema de almacenamiento de energía (baterías) y un sistema de almacenamiento de energía híbrido (baterías y supercapacitores), considerando diferentes problemas de optimización mono-objetivo y multi-objetivo. Con base en los resultados de cada problema de optimización, se procede a realizar un análisis comparativo con un elemento de acumulación comercial. Considerando un tren de potencia eléctrico híbrido que integra un sistema de almacenamiento de energía híbrido (baterías y supercapacitores), se desarrolla una estrategia de gestión de energía basada en lógica difusa, que incluye la identificación del estado del vehículo a partir de un ciclo de conducción real. Finalmente, se realiza la validación de la estrategia de gestión de energía a través del modelo de un vehículo eléctrico híbrido de recolección de basura.Postprint (published version

Aportaciones al dimensionamiento y gestión de energía de un tren de potencia eléctrico híbrido para vehículos industriales con ciclos de conducción repetitivos y agresivos

Currently, the interest for helping mitigate the emission of greenhouse gases caused by high fuel consumption in industrial vehicles has increased. In order to the reduction of fuel consumption in an industrial vehicle, it has been proposed to incorporate into the powertrain a system capable of storing and supplying electrical energy. Consequently, the design of a hybrid electric powertrain is required, based on the interconnection of the elements (topology), the sizing of the elements and/or the energy management strategy of the powertrain. This paper presents a methodology for the design of a hybrid electric vehicle for refuse collection, which presents a repetitive and aggressive drive cycle as a result of work activity. The proposed methodology consists in modeling the behavior of a hybrid electric powertrain, considering the electrical behavior of various energy accumulation elements (batteries and supercapacitors). An embedded system is used to perform the experimental characterization of a cell and a commercial supercapacitor, in order to approximate the behavior through an electric model. In accordance with a real drive cycle of a refuse collection vehicle, the energy demand for a hybrid electric refuse collection vehicle is determined. On the other hand, the fuel consumption is calculated from a hybrid electric powertrain that integrates an energy storage system or a hybrid energy storage system. A bio-inspired metaheuristic based on a stochastic population (particle swarm optimization and genetic algorithm) is developed, in order to determine an optimal solutions space. Subsequently, the optimal sizing of an energy storage system (batteries) and a hybrid energy storage system (batteries and supercapacitors) is performed, considering different mono-objective and multi-objective optimization problems. Based on the results of each optimization problem, a comparative analysis is carried out with an element of commercial accumulation. Considering a hybrid electric powertrain that integrates a hybrid energy storage system (batteries and supercapacitors), an energy management strategy based on fuzzy logic is developed. This includes the identification of the vehicle status from a real drive cycle. Finally, the validation of the energy management strategy is carried out through the model of a hybrid electric vehicle for refuse collection.Actualmente, se ha incrementado el interés por mitigar la emisión de gases de efecto invernadero que se produce por un elevado consumo de combustible en vehículos industriales. Con la intención de contribuir en la reducción del consumo de combustible de un vehículo industrial, se ha propuesto incorporar al tren de potencia un sistema capaz de almacenar y suministrar energía eléctrica. En consecuencia, surge la necesidad de realizar el diseño de un tren de potencia eléctrico híbrido, a partir de la interconexión de los elementos (topología), el dimensionamiento de los elementos y/o la estrategia de gestión de energía del tren de potencia. En el presente trabajo se presenta una metodología para realizar el diseño de un vehículo eléctrico híbrido de recolección de basura, que presenta un ciclo de conducción repetitivo y agresivo como resultado de la actividad laboral. La metodología propuesta consiste en modelar el comportamiento de un tren de potencia eléctrico híbrido, considerando el comportamiento eléctrico de diversos elementos de acumulación de energía híbrido (baterías y supercapacitores). Se emplea un sistema embebido para realizar la caracterización experimental de una celda y un supercapacitor comercial, con el propósito de aproximar el comportamiento a través de un modelo eléctrico. En función de un ciclo de conducción real de un vehículo de recolección de basura se determina la demanda de energía para un vehículo eléctrico híbrido de recolección de basura. Por otra parte, se calcula el consumo de combustible a partir de un tren de potencia eléctrico híbrido que integra un sistema de almacenamiento de energía o un sistema de almacenamiento de energía híbrido. Se desarrolla una metaheurística bio-inspirada basada en una población estocástica) para determinar un espacio de soluciones óptimas. Posteriormente, se realiza el dimensionamiento óptimo de un sistema de almacenamiento de energía (baterías) y un sistema de almacenamiento de energía híbrido (baterías y supercapacitores), considerando diferentes problemas de optimización mono-objetivo y multi-objetivo. Con base en los resultados de cada problema de optimización, se procede a realizar un análisis comparativo con un elemento de acumulación comercial. Considerando un tren de potencia eléctrico híbrido que integra un sistema de almacenamiento de energía híbrido (baterías y supercapacitores), se desarrolla una estrategia de gestión de energía basada en lógica difusa, que incluye la identificación del estado del vehículo a partir de un ciclo de conducción real. Finalmente, se realiza la validación de la estrategia de gestión de energía a través del modelo de un vehículo eléctrico híbrido de recolección de basura