A state-of-the-art review on torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains

© 2019, Levrotto and Bella. All rights reserved. Electric vehicles are the future of private passenger transportation. However, there are still several technological barriers that hinder the large scale adoption of electric vehicles. In particular, their limited autonomy motivates studies on methods for improving the energy efficiency of electric vehicles so as to make them more attractive to the market. This paper provides a concise review on the current state-of-the-art of torque distribution strategies aimed at enhancing energy efficiency for fully electric vehicles with independently actuated drivetrains (FEVIADs). Starting from the operating principles, which include the "control allocation" problem, the peculiarities of each proposed solution are illustrated. All the existing techniques are categorized based on a selection of parameters deemed relevant to provide a comprehensive overview and understanding of the topic. Finally, future concerns and research perspectives for FEVIAD are discussed

Multi-level decision framework collision avoidance algorithm in emergency scenarios

With the rapid development of autonomous driving, the attention of academia has increasingly focused on the development of anti-collision systems in emergency scenarios, which have a crucial impact on driving safety. While numerous anti-collision strategies have emerged in recent years, most of them only consider steering or braking. The dynamic and complex nature of the driving environment presents a challenge to developing robust collision avoidance algorithms in emergency scenarios. To address the complex, dynamic obstacle scene and improve lateral maneuverability, this paper establishes a multi-level decision-making obstacle avoidance framework that employs the safe distance model and integrates emergency steering and emergency braking to complete the obstacle avoidance process. This approach helps avoid the high-risk situation of vehicle instability that can result from the separation of steering and braking actions. In the emergency steering algorithm, we define the collision hazard moment and propose a multi-constraint dynamic collision avoidance planning method that considers the driving area. Simulation results demonstrate that the decision-making collision avoidance logic can be applied to dynamic collision avoidance scenarios in complex traffic situations, effectively completing the obstacle avoidance task in emergency scenarios and improving the safety of autonomous driving

Non-visual Effects of Road Lighting CCT on Driver's Mood, Alertness, Fatigue and Reaction Time: A Comprehensive Neuroergonomic Evaluation Study

Good nighttime road lighting is critical for driving safety. To improve the quality of nighttime road lighting, this study used the triangulation method by fusing "EEG evaluation + subjective evaluation + behavioral evaluation" to qualitatively and quantitatively investigate the response characteristics of different correlated color temperature (CCT) (3500K, 4500K, 5500K, 6500K) on drivers' non-visual indicators (mood, alertness, fatigue and reaction time) under specific driving conditions (monotonous driving; waiting for red light and traffic jam; car-following task). The results showed that the CCT and Task interaction effect is mainly related to individual alertness and reaction time. Individual subjective emotional experience, subjective visual comfort and psychological security are more responsive to changes in CCT than individual mental fatigue and visual fatigue. The subjective and objective evaluation results demonstrated that the EEG evaluation indices used in this study could objectively reflect the response characteristics of various non-visual indicators. The findings also revealed that moderate CCT (4500K) appears to be the most beneficial to drivers in maintaining an ideal state of mind and body during nighttime driving, which is manifested as: good mood experience; it helps drivers maintain a relatively stable level of alterness and to respond quickly to external stimuli; both mental and visual fatigue were relatively low. This study extends nighttime road lighting design research from the perspective of non-visual effects by using comprehensive neuroergonomic evaluation methods, and it provides a theoretical and empirical basis for the future development of a humanized urban road lighting design evaluation system.Comment: 38 pages, 15 figures, 103 conference

DETECTION PROCESS OF ENERGY LOSS IN ELECTRIC RAILWAY VEHICLES

The paper deals with the detection process of energy loss in electric railway hauling vehicles. The importance of efficient energy use in railways and cost-effective rail transport tendency toward regenerative braking energy are considered. In addition, the current situation and improvement opportunities to achieve efficient energy use are examined. Seven measurement series were performed with scheduled Railjet trains between Hegyeshalom and Győr railway stations in Hungary. This railway section is related to the Hungarian State Railways' No. 1 main railway line (between Budapest-Kelenföld and Hegyeshalom state board), which is a part of the international railway line between Budapest and Vienna (capitals of Hungary and Austria, respectively). This double-track, electrified railway line with traditional ballasted superstructures and continuously welded rail tracks is important due to the international passenger and freight transport between Germany, Austria, and Hungary. The value of the regenerative braking energy can be even 20-30% of the total consumed energy. This quite enormous untapped energy can be used for several aims, e.g., for comfort energy demand (air conditioning, heating-cooling, lighting, etc.) or energy-intensive starts. The article also investigates the optimization of regenerative braking energy by seeking the energy-waste locations and the reasons for the significant consumption. The train operator's driving style and habit have been identified as one of the main reasons. Furthermore, train driver assistance systems are recommended to save energy, which is planned for future research

A Comparative Study on Developing the Hybrid-Electric Vehicle ‎Systems and its Future Expectation over the Conventional Engines Cars

The use of hybrid electric vehicles (HEVs) as an alternative to traditional petroleum-powered cars has risen due to climate change, air pollution, and fuel depletion. The transportation sector is the second largest energy-consuming sector that accounts for 30% of the world’s total delivered energy and about 60% of world oil demand. In 2008, the transportation sector accounted for about 22% of total world CO2 emissions. Within this sector, road vehicles dominate oil consumption and represent 81% of total transportation energy demand. This review discusses opportunities to reduce energy consumed and greenhouse gases in this sector and briefly discusses the Hybrid electric vehicles as a solution to improve fuel economy and reduce emissions. Also, the Classification of Hybrid Electric Vehicles, and the General architectures of hybrid electric vehicles and their subtypes have been discussed. Hybrid electric vehicle system components, system analysis, and fuel economy benefits are also explained. As the comparison results proved that the benefits of improved engine thermal efficiency outweigh the losses caused by longer energy transmission paths and showed that hybridization can improve fuel economy by about 24% in typical urban cycles. This study offers a thorough analysis of hybrid electric vehicles, including information on the designs, and energy management systems, created by different researchers. According to the thorough analysis, the current systems can execute HEVs rather effectively, but their dependability and autonomous systems remain not satisfactory. Several variables, difficulties, and issues related to the future generation of hybrid cars have been highlighted in this research

Intelligent energy management in hybrid electric vehicles

The modelling and simulation approach is employed to develop an intelligent energy management system for hybrid electric vehicles. The aim is to optimize fuel consumption and reduce emissions. An analysis of the role of drivetrain, energy management control strategy and the associated impacts on the fuel consumption with combined wind/drag, slope, rolling, and accessories loads are included.<br /

Control systems integration for enhanced vehicle dynamics

This paper deals with improving comfort and handling for a ground vehicle through the coordinated control of different active systems available in passenger cars, e.g., electronic stability control, active roll control and engine torque control. The authors first describe separate control systems, each with its logic, showing advantages and limits, then propose various possible integrations, aiming at exploiting the benefits of a coordinated approach. Finally, the proposed control logics are tested on a vehicle model: simulation results prove the effectiveness of the approach in improving vehicle response during typical handling maneuver

Development of an Advanced Fuzzy Active Steering Controller and a Novel Method to Tune the Fuzzy Controller

Replicated with permission by SAE Copyright © 2017 SAE International. Further distribution of this material is not permitted without prior permission from SAE.A two-passenger, all-wheel-drive urban electric vehicle (AUTO21EV) with four direct-drive in-wheel motors has been designed and developed at the University of Waterloo. An advanced genetic-fuzzy active steering controller is developed based on this vehicle platform. The rule base of the fuzzy controller is developed from expert knowledge, and a multi-criteria genetic algorithm is used to optimize the parameters of the fuzzy active steering controller. To evaluate the performance of this controller, a computational model of the AUTO21EV is driven through several standard test maneuvers using an advanced path-following driver model. As the final step in the evaluation process, the genetic-fuzzy active steering controller is implemented in a hardware- and operator-in-the-loop driving simulator to confirm its performance and effectiveness.Funding for this work was provided by the Natural Sciences and Engineering Research Council of Canada and agrant from AUTO21, a Canadian Network of Centres of Excellenc

A Case of Trailer Selection under Fuzzy Environment via PIPRECIA Extended and CoCoSo Methods

The trailer, which is defined as the part behind the chassis in vehicles, is widely used especially in road transportation and allows the simultaneous transfer of large volume product groups. Different types of trailers produced for different needs enable logistics companies and manufacturers to have suitable transportation options for the transfer they need. This study aims to solve a trailer selection problem, which has strategic importance for transportation companies. Thereforen, the criteria that are important in the selection of the trailer are chosen and their weights are calculated via Fuzzy PIPRECIA-Extended. Thereafter, alternatives were evaluated using the Fuzzy CoCoSo method. The results showed that the most essential criterion in the selection of the trailer is found out as “Light structure”, and the most appropriate trailer is obtained as the Tırsan.SCL X / 150 - 12/27 Trailer. According to the findings, comprehensive perspectives related to the trailer selection problem is presented. This study will benefit the literature in terms of both application and the integrated methods