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

Urban and extra-urban hybrid vehicles: a technological review

Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use (implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used

In-wheel motor design for electric vehicles

In this work an in-wheel electric motor prototype has been designed for experimental purposes. In-Wheel Motor (Hub motor) can be used in electric cars with 4 wheel independent drive configuration. Within every wheel, there can be one “Direct-Drive In-Wheel Motor” to generate the necessary torque per wheel. Unlike conventional “central drive unit” systems, torque as well as the power and speed can be supplied to each tire independently. The difference in this work is the design of a direct drive electric motor which is able to carry transverse loading acts on a tire. Type of the motor is called inverted configuration or outer rotor structure in the literature. The electric machine designed in this work is Switched Reluctance Machine. First a 3D solid model was created. Necessary strength analyses have been done. Simultaneously, electromagnetic FEA has been done, when it is necessary either of the designs were modified until it converged to a set of consistent dimensions for both mechanic and electromagnetic design. Last, the results of the electromagnetic analysis were embedded into a hybrid simulation model, in order to check the coherency between the design and the analysis. The results were coherent

Transport and energy in India. Energy used by Indian transport systems and consequent emissions: the need for quantitative analyses (Well-to-Wheel, Lifecycle)

The purpose of this work is, at first, a general overview on the state-of-art of the transportation system in India outlining the related energy consumption, for the different transport modes, with consequent estimated emissions. These elements are essential for the preparation of a high-level strategic transport planning on the whole energy issue, to help India in the choices of most suitable transportation systems, according to the well-to-wheel analysis (WTW). Pursuing a WTW global index for India that takes into account both the energy and environmental aspects on a uniform basis is an important aim: it allows the best choices to be made as well as enabling the comparison between some of the most important powertrain and fuel options on the Indian market, the results are discussed from three different points of view: energy, environmental and economic impac

Phase 1 of the near term hybrid passenger vehicle development program

In order to meet project requirements and be competitive in the 1985 market, the proposed six-passenger vehicle incorporates a high power type Ni-Zn battery, which by making electric-only traction possible, permits the achievement of an optimized control strategy based on electric-only traction to a set battery depth of discharge, followed by hybrid operation with thermal primary energy. This results in a highly efficient hybrid propulsion subsystem. Technical solutions are available to contain energy waste by reducing vehicle weight, rolling resistance, and drag coefficient. Reproaching new 1985 full size vehicles of the conventional type with hybrids of the proposed type would result in a U.S. average gasoline saving per vehicle of 1,261 liters/year and an average energy saving per vehicle of 27,133 MJ/year

Benchmarking of a software stack for autonomous racing against a professional human race driver

The way to full autonomy of public road vehicles requires the step-by-step replacement of the human driver, with the ultimate goal of replacing the driver completely. Eventually, the driving software has to be able to handle all situations that occur on its own, even emergency situations. These particular situations require extreme combined braking and steering actions at the limits of handling to avoid an accident or to diminish its consequences. An average human driver is not trained to handle such extreme and rarely occurring situations and therefore often fails to do so. However, professional race drivers are trained to drive a vehicle utilizing the maximum amount of possible tire forces. These abilities are of high interest for the development of autonomous driving software. Here, we compare a professional race driver and our software stack developed for autonomous racing with data analysis techniques established in motorsports. The goal of this research is to derive indications for further improvement of the performance of our software and to identify areas where it still fails to meet the performance level of the human race driver. Our results are used to extend our software's capabilities and also to incorporate our findings into the research and development of public road autonomous vehicles.Comment: Accepted at 2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER

Implementing a hybrid series bus with gas turbine device - a preliminary study

This paper presents the implementation of an hybrid series Bus with a gas turbine, as thermal engine. The hybridization methodology for transforming city buses, substituting the original gasoline/diesel engine with a micro gas turbine device (intended as range extender), into a series hybrid vehicle has investigated and its feasibility analyzed. The study was conducted by the university of Rome “Sapienza” in collaboration with several enterprises. The idea is to design a hybrid power train that can be installed in a typical city bus, which means that all systems and components will be influenced by the limited space available. In this paper the details of the mechanical and electrical realization of the power train will be discussed. The hybrid system also includes consideration on the battery pack and the vehicle management logic. The proposed solution obtains a reduction in fuel consumption higher than 20%, in comparison with normal commercial fleet

Efficient Neural Network Implementations on Parallel Embedded Platforms Applied to Real-Time Torque-Vectoring Optimization Using Predictions for Multi-Motor Electric Vehicles

The combination of machine learning and heterogeneous embedded platforms enables new potential for developing sophisticated control concepts which are applicable to the field of vehicle dynamics and ADAS. This interdisciplinary work provides enabler solutions -ultimately implementing fast predictions using neural networks (NNs) on field programmable gate arrays (FPGAs) and graphical processing units (GPUs)- while applying them to a challenging application: Torque Vectoring on a multi-electric-motor vehicle for enhanced vehicle dynamics. The foundation motivating this work is provided by discussing multiple domains of the technological context as well as the constraints related to the automotive field, which contrast with the attractiveness of exploiting the capabilities of new embedded platforms to apply advanced control algorithms for complex control problems. In this particular case we target enhanced vehicle dynamics on a multi-motor electric vehicle benefiting from the greater degrees of freedom and controllability offered by such powertrains. Considering the constraints of the application and the implications of the selected multivariable optimization challenge, we propose a NN to provide batch predictions for real-time optimization. This leads to the major contribution of this work: efficient NN implementations on two intrinsically parallel embedded platforms, a GPU and a FPGA, following an analysis of theoretical and practical implications of their different operating paradigms, in order to efficiently harness their computing potential while gaining insight into their peculiarities. The achieved results exceed the expectations and additionally provide a representative illustration of the strengths and weaknesses of each kind of platform. Consequently, having shown the applicability of the proposed solutions, this work contributes valuable enablers also for further developments following similar fundamental principles.Some of the results presented in this work are related to activities within the 3Ccar project, which has received funding from ECSEL Joint Undertaking under grant agreement No. 662192. This Joint Undertaking received support from the European Union’s Horizon 2020 research and innovation programme and Germany, Austria, Czech Republic, Romania, Belgium, United Kingdom, France, Netherlands, Latvia, Finland, Spain, Italy, Lithuania. This work was also partly supported by the project ENABLES3, which received funding from ECSEL Joint Undertaking under grant agreement No. 692455-2

Advanced electric propulsion system concept for electric vehicles. Addendum 1: Voltage considerations

The two electric vehicle propulsion systems that best met cost and performance goals were examined to assess the effect of battery pack voltage on system performance and cost. A voltage range of 54 to 540 V was considered for a typical battery pack capacity of 24 k W-hr. The highest battery specific energy (W-hr/kg) and the lowest cost ($/kW-hr) were obtained at the minimum voltage level. The flywheel system traction motor is a dc, mechanically commutated with shunt field control, and due to the flywheel the traction motor and the battery are not subject to extreme peaks of power demand. The basic system uses a permanent-magnet motor with electronic commutation supplied by an ac power control unit. In both systems battery cost were the major factor in system voltage selection, and a battery pack with the minimum voltage of 54 V produced the lowest life-cycle cost. The minimum life-cycle cost for the basic system with lead-acid batteries was$0.057/km and for the flywheel system was $0.037/km