Trends and Technical Advancements on High-Efficiency Electric Motors: A Review

Faiz, Jawad; Parvin, Farbod

doi:10.1007/978-3-030-69288-9_5

Cited by 2 publications

References 46 publications

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Conflict-free and energy-efficient path planning for multi-robots based on priority free ant colony optimization

Yang

2022

MBE

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<abstract><p>With the background of limited energy storage of robots and considering the high coupling problem of multi-agent path finding (MAPF), we propose a priority-free ant colony optimization (PFACO) to plan conflict-free and energy-efficient paths, reducing multi-robots motion cost in the rough ground environment. First, a dual-resolution grid map considering obstacles and ground friction factors is designed to model the unstructured rough terrain. Second, an energy-constrained ant colony optimization (ECACO) is proposed to achieve energy-optimal path planning for a single robot, in which we improve the heuristic function based on the combined effects of path length, path smoothness, ground friction coefficient and energy consumption, and consider multiple energy consumption metrics during robot motion to improved pheromone update strategy. Finally, considering multiple collision conflict cases among multiple robots, we incorporate a prioritized conflict-free strategy (PCS) and a route conflict-free strategy (RCS) based on ECACO to achieve MAPF with low-energy and conflict-free in a rough environment. Simulation and experimental results show that ECACO can achieve better energy saving for single robot motion under all three common neighborhood search strategies. PFACO achieves both the conflict-free path and energy-saving planning for robots in complex scenarios, and the study has some reference value for solving practical problems.</p></abstract>

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Conflict-free and energy-efficient path planning for multi-robots based on priority free ant colony optimization

Yang

2022

MBE

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A Novel Model-Based Approach for Evaluating Multi-Speed Transmission Systems for BEVs

Skarlis¹,

Molos²

2023

SAE Technical Paper Series

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<div class="section abstract"><div class="htmlview paragraph">State of the art battery electric vehicles (BEVs) become increasingly attractive, thanks to their top performance and high energy efficiency. Nevertheless, despite improvements in electric motors efficiency and motive batteries technology, there is still space for improving BEVs’ autonomy. Among others, use of a multi-speed, instead of a single-speed transmission system has the potential to optimize BEV’s energy consumption and driving range. In this respect, the scope of this work is to demonstrate a novel model-based approach for evaluating the potential of multi-speed gear box technology. For this purpose, advanced vehicle modeling was combined with statistical analysis tools and an optimization algorithm, with an aim to optimize gear ratios and the respective gear shifting strategy, ultimately maximizing BEV’s autonomy and performance. Respective results allow for an in-depth analysis of the multi-speed transmission system, already at early stages of a BEV development, which can eventually minimize battery electric powertrain system design time and cost.</div></div>

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Trends and Technical Advancements on High-Efficiency Electric Motors: A Review

Cited by 2 publications

References 46 publications

Conflict-free and energy-efficient path planning for multi-robots based on priority free ant colony optimization

Conflict-free and energy-efficient path planning for multi-robots based on priority free ant colony optimization

A Novel Model-Based Approach for Evaluating Multi-Speed Transmission Systems for BEVs

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