Energy Consumption Analysis of Different Bev Powertrain Topologies by Design Optimization

Wang, Bin; Hung, David L.S.; Zhong, Jie; Teh, Kwee-Yan

doi:10.1007/s12239-018-0087-z

Cited by 28 publications

(9 citation statements)

References 24 publications

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“…The accuracy of the simulation with respect to the results obtained in the NEDC (135 Wh/km) and EPA (179 Wh/km) tests was below 6%. Another modelling procedure [46], using three different electric drive system configurations in terms of NEDC and Japanese JC08 tests, allowed determination of the minimum vehicle energy consumption in the range of 81.5-97.9 Wh/km depending on the system configuration and the test performed. A small deviation from the real results (5%) was obtained [47] by optimizing the results from driving tests, road information, and geographical and weather data using a genetic algorithm.…”

Section: Energy Consumption Of Electric Vehicle In Real Driving Conditions (Rdc)mentioning

confidence: 99%

Capabilities of Nearly Zero Energy Building (nZEB) Electricity Generation to Charge Electric Vehicle (EV) Operating in Real Driving Conditions (RDC)

et al. 2021

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The growing number of electric vehicles in recent years is observable in almost all countries. The country’s energy transition should accompany this rise in electromobility if it is currently generated from non-renewable sources. Only electric vehicles powered by renewable energy sources can be considered zero-emission. Therefore, it is essential to conduct interdisciplinary research on the feasibility of combining energy recovery/generation structures and testing the energy consumption of electric vehicles under real driving conditions. This work presents a comprehensive approach for evaluating the energy consumption of a modern public building–electric vehicle system within a specific location. The original methodology developed includes surveys that demonstrate the required mobility range to be provided to occupants of the building under consideration. In the next step, an energy balance was performed for a novel near-zero energy building equipped with a 199.8 kWp photovoltaic installation, the energy from which can be used to charge an electric vehicle. The analysis considered the variation in vehicle energy consumption by season (winter/summer), the actual charging profile of the vehicle, and the parking periods required to achieve the target range for the user.

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Section: Energy Consumption Of Electric Vehicle In Real Driving Conditions (Rdc)mentioning

confidence: 99%

Capabilities of Nearly Zero Energy Building (nZEB) Electricity Generation to Charge Electric Vehicle (EV) Operating in Real Driving Conditions (RDC)

et al. 2021

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“…A few publications considered optimizing the components' sizing for a single or a few topologies [10,15,16], often combined with the control optimization. Only limited research seems to focus specifically on the variation of the powertrain topology for all-electric vehicles; with limited examples that can be found either focused on hybrid electric vehicles [17][18][19][20] (e.g., where the focus is limited to the type of hybrid powertrain: series, parallel or power split) or the research is limited to the light-duty vehicle domain [21][22][23][24][25]. Therefore, there is little knowledge on the influence of topological design choices for full battery electric powertrains for heavy-duty trucks, which is crucial in order to evaluate the full potential of these type of vehicles.…”

Section: System-level Designmentioning

confidence: 99%

Electric Powertrain Topology Analysis and Design for Heavy-Duty Trucks

2020

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Powertrain system design optimization is an unexplored territory for battery electric trucks, which only recently have been seen as a feasible solution for sustainable road transport. To investigate the potential of these vehicles, in this paper, a variety of new battery electric powertrain topologies for heavy-duty trucks is studied. Thereby, topological design considerations are analyzed related to having: (a) a central or distributed drive system (individually-driven wheels); (b) a single or a multi-speed gearbox; and finally, (c) a single or multiple electric machines. For reasons of comparison, each concurrent powertrain topology is optimized using a bilevel optimization framework, incorporating both powertrain components and control design. The results show that the combined choice of powertrain topology and number of gears in the gearbox can result in a 5.6% total-cost-of-ownership variation of the vehicle and can, significantly, influence the optimal sizing of the electric machine(s). The lowest total-cost-of-ownership is achieved by a distributed topology with two electric machines and two two-speed gearboxes. Furthermore, results show that the largest average reduction in total-cost-of-ownership is achieved by choosing a distributed drive over a central drive topology (−1.0%); followed by using a two-speed gearbox over a single speed (−0.6%); and lastly, by using two electric machines over using one for the central drive topologies (−0.3%).

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“…In the economic development of energy, based on the huge economic value of energy products, the energy structure optimization can improve the energy sustainable development ability and lay the foundation for social stability and the improvement of national living standards. Energy is the process of economic activities for those material resources that can produce heat and energy [7]. ese energy sources cover a wide range and have many kinds, such as renewable energy sources such as new energy sources, petrochemical energy sources, and natural gas energy sources.…”

Section: Introductionmentioning

confidence: 99%

Energy Economy and Energy Structure Optimization Countermeasures Based on Big Data Mining

Zhang

Lin

2022

Wireless Communications and Mobile Computing

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The impact of energy on the economy must be examined not only from an energy structure standpoint but also from an economic structure standpoint, as there is a close relationship between energy structure and energy economy. To avoid the negative effects of energy consumption on the economy, it is also necessary to assess the constraints to the development of the energy economy and then optimize the energy economy and energy structure to achieve rapid economic growth. The research object in this paper is a data center powered by renewable energy, and the resource and energy consumption management model and algorithm are examined. Different adaptive scheduling algorithms are designed for different emphases, and an approximate application scheduling algorithm for renewable energy utilization based on DM is proposed. When building a data center, researching the resource management and energy consumption management strategies can help determine the best energy access scheme. It can provide the necessary reference for specific planning, such as software and hardware configuration, equipment parameter determination, and power access, resulting in lower construction and operation costs.

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Energy Consumption Analysis of Different Bev Powertrain Topologies by Design Optimization

Cited by 28 publications

References 24 publications

Capabilities of Nearly Zero Energy Building (nZEB) Electricity Generation to Charge Electric Vehicle (EV) Operating in Real Driving Conditions (RDC)

Capabilities of Nearly Zero Energy Building (nZEB) Electricity Generation to Charge Electric Vehicle (EV) Operating in Real Driving Conditions (RDC)

Electric Powertrain Topology Analysis and Design for Heavy-Duty Trucks

Energy Economy and Energy Structure Optimization Countermeasures Based on Big Data Mining

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