Design, Analysis, and Optimization of a Multi-Speed Powertrain for Class-7 Electric Trucks

Morozov, Alexei A.; Humphries, Kieran; Zou, Ting; Rahman, Tanvir; Ángeles, Jorge

doi:10.4271/08-07-01-0002

Cited by 14 publications

(21 citation statements)

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“…In the context of battery electric trucks, most literature focuses on the feasibility [4][5][6][7][8] or performance evaluation [9] analyses. In addition, some recent research has focused on the type of technology used for the components, in particular focusing on: (i) the electric machine technology [10], (ii) battery technology [11,12], or (iii) the transmission technology [10,[13][14][15]. A few publications considered optimizing the components' sizing for a single or a few topologies [10,15,16], often combined with the control optimization.…”

Section: System-level Designmentioning

confidence: 99%

“…In addition, some recent research has focused on the type of technology used for the components, in particular focusing on: (i) the electric machine technology [10], (ii) battery technology [11,12], or (iii) the transmission technology [10,[13][14][15]. 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].…”

Section: System-level Designmentioning

confidence: 99%

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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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Section: System-level Designmentioning

confidence: 99%

Section: System-level Designmentioning

confidence: 99%

Electric Powertrain Topology Analysis and Design for Heavy-Duty Trucks

2020

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“…For a current review of electric vehicle drivetrain efficiency see [17]. Also, [18] considers electric drivetrains specifically for heavy road vehicles.…”

Section: Scope and Limitationsmentioning

confidence: 99%

Efficiency of an AC Conductive In-Road Charging System for Electric Vehicles-Analysis of Pilot Project Data

Hellgren¹,

Honeth²

2020

SAE Int. J. Alt. Power.

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This article describes the conductive inroad charging system as developed in the eRoadArlanda project, a pilot project for the development of inroad charging system for both heavy and light vehicles intended for application in motorways. The results of an analysis of measurements collected during the integration tests of this system are presented and discussed. The results focus on the end-to-end efficiency of the inroad charging system and aim to provide researchers in the field with a reference for this technology and configuration for use in the future development of such infrastructure. The analysis of the measurement data addresses losses in the low-voltage side of the AC conductive charging system as well as the vehicle-mounted isolated rectifier/converter connected to the vehicle DC system. An exploratory analysis of data collected over a 6-month testing period in varying weather conditions is used to provide insight into factors affecting the overall efficiency of the system. A discussion of the results includes the effects of cable dimensioning, rectifier performance and placement, and the use of salt for deicing.

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“…One of the key factors of overall efficiency maximization covers the well-sized and high-efficient components [19][20][21][22]. Therefore, the reduction and prediction of faults occurring in electrical machines and drive systems such as electrical, thermal, and mechanical faults of electrical machines are strongly suggested to be essential [23][24][25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis of Rotating Electrical Machines Using Multi-Label Classification

et al. 2019

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Fault Detection and Diagnosis of electrical machine and drive systems are of utmost importance in modern industrial automation. The widespread use of Machine Learning techniques has made it possible to replace traditional motor fault detection techniques with more efficient solutions that are capable of early fault recognition by using large amounts of sensory data. However, the detection of concurrent failures is still a challenge in the presence of disturbing noises or when the multiple faults cause overlapping features. Multi-label classification has recently gained popularity in various application domains as an efficient method for fault detection and monitoring of systems with promising results. The contribution of this work is to propose a novel methodology for multi-label classification for simultaneously diagnosing multiple faults and evaluating the fault severity under noisy conditions. In this research, the Electrical Signature Analysis as well as traditional vibration data have been considered for modeling. Furthermore, the performance of various multi-label classification models is compared. Current and vibration signals are acquired under normal and fault conditions. The applicability of the proposed method is experimentally validated under diverse fault conditions such as unbalance and misalignment.

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Design, Analysis, and Optimization of a Multi-Speed Powertrain for Class-7 Electric Trucks

Cited by 14 publications

References 0 publications

Electric Powertrain Topology Analysis and Design for Heavy-Duty Trucks

Electric Powertrain Topology Analysis and Design for Heavy-Duty Trucks

Efficiency of an AC Conductive In-Road Charging System for Electric Vehicles-Analysis of Pilot Project Data

Fault Diagnosis of Rotating Electrical Machines Using Multi-Label Classification

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