Abstract

We investigate the impact of massive electric vehicle (EV) adoption onto the power market, both in the presence and in the absence of significant photovoltaic (PV) generation. Although results are derived taking into consideration Italys power market, results are of relevance also to other industrialized countries. One of the most important outcomes of the analysis, that is, the synergistic and beneficial effect on the overall energy bill of the concomitant expansion of EVs utilization and the growth of the renewable energy generation, particularly solar photovoltaics. The Conclusions provide arguments for policymakers for further support to sustainable mobility in their regions.

Abstract

Population growth in the world had a constant value since the beginning of a new era to the 19th century when the population was 1 billion. The technological revolution is largely in? fluenced by that in this century, the population increase by 68 %. The population in the world increased by about 270 %, or over 6 billion people just in the 20 century. Although the UN in [1], estimates three possible scenarios of population growth in this century, the pic? ture 1, is the most possible one that predicts that the world population will increase by 2050. to about 8,9 billion, and afterwards it will be a slowdown so that by the end of the 21st cen? tury, and in the next few, does not expect the growth of population in the country. In any case, in the near future over the next four decades strong growth of the population is expect? ed. With the growth of population in the world there is a need to increase transportation of people, goods and raw materials as a prerequisite for the growth of production and con? sumption and the standards of living. Document type: Part of book or chapter of book

Abstract

Many auto manufacturers are now producing hybrid and electric vehicles with an additive noise component to signal vehicle presence in the same way that internal combustion engine vehicles signal their presence through engine noise. The Virginia Tech Transportation Institute conducted an evaluation of quiet car detectability as part of a GM-funded project in 2015–2016. The internal combustion engine benchmark significantly outperformed the other three vehicles under a 10-km/h steady approach, but these differences largely disappeared at 20 km/h due to increased tire and road noise. Trends of improved detectability offered by the additive noise signals were observed but did not demonstrate a significant advantage over an electric vehicle with no additional noise component. Since that original project, NHTSA has released their final version of Federal Motor Vehicle Safety Standard (FMVSS) 141, outlining “Minimum Sound Requirements for Hybrid and Electric Vehicles.” This project aimed to demonstrate differences in detectability by replicating the previous study but with newer FMVSS 141-compliant sounds. The proposed additive sounds examined drastically improved detectability compared to the production variants included in the first round of testing. At 10 km/h, the additive sound conditions outperformed the no-sound condition by magnitudes ranging from 3.4 to 4.6, each eliciting mean detection distances well above the NHTSA minimum detection criteria. At 20 km/h, detectability also improved dramatically over the earlier production variants, achieving a similar magnitude advantage over no-sound as observed at 10 km/h. Increasing background noise resulted in a measurable impact on mean detection distances. The average reduction across all conditions was approximately 33% and 28% for approach speeds of 10 km/h and 20 km/h, respectively. In terms of accurately recognizing a stopped vehicle in a 20 to 0 km/h scenario, all sound conditions significantly outperformed the no-sound condition across both background noise conditions.

Abstract

This paper introduces the development and calibration process of a vehicle drivetrain observer used in hybrid and electric vehicles for active damping control (ADC) and for the improvement of the electric machine’s rotor angle signal quality. This approach starts with creating an overall vehicle model that includes the electric machine, the transmission, side shafts, the tires and the vehicle body. For control engineering purposes, that multi-order-model is then reduced into a two-mass-oscillator which can be easily described in state-space form. Using this reduced drivetrain model and applying a Luenberger observer approach, not only the signal quality of both the instrumented rotor angle and the speed of the electric machine can be improved considerably but also the oscillation dynamics of this vehicle drivetrain can be estimated. If not compensated during vehicle operation, drivetrain oscillations might lead to increased drivetrain wear, NVH issues and limited ride comfort therefore, the oscillation speed is very important in computing an active damping torque that is to compensate drivetrain oscillations. Calibration of the vehicle drivetrain observer is done using specific vehicle test data that are fed into a standalone calibration tool identifying the parameters of the vehicle drivetrain as well as the Luenberger feedback vector. Based on these data, a proper active damping control application is set-up and verified in various vehicle tests and to lead to the calibration finally to the application in several hybrid and electric vehicle series projects (e.g. Peugeot 3008 HYbrid4). Document type: Article

Abstract

The major advantages of electric propulsion compared to conventional power transmission drive of diesel engine to the wheels are presented and explained. It is in briefly showed development of some electrical vehicles in our country. The analysis of the electric drive showed some advantages of electric propulsion, such as operation without thermo emission of the vehicle, improved maneuvering and noiseless operating of the vehicle and saving fossil fuel. For any applications, hybrid vehicles have some good features of electric drive and vehicles with IC engines. Some military applications in the world of electric vehicle will be shown in this paper.

Abstract

First EV has been made in in 1837. This type of motor vehicles has dominated throughout the whole 19th century. In the early 20th century the faster and more robust vehicles with ICE overcame them until late 20th century, when ecological and economic problems of further application of these vehicles have emerged. The interest in EV has risen sharply. Researches are working in several directions in order to reduce the need for oil derivatives considering that the EV's are weak primarily due to inferior "reservoir of energy" to fully meet the current driving habits. Savings can be achieved in two ways, by making more economic motor vehicles or by the use of alternative fuels. Combining an electric propulsion and IC engine drives a hybrid vehicle is obtained, with a greater amount of batteries and "plug in" that is to some extent possible to reduce fossil fuel consumption and exhaust emissions. Intensive research work on exploring new battery is still to come. Today promising results with Li - air batteries, fuel cells and super capacitors, as well as the efforts of major car manufacturers indicate that the EV could soon appear massive in the streets of cities. This paper deals with the development of EV, following the development of powertrain and can conclude the fact that in the near future this type of drive could return.

Abstract

International audience; In this study a new concept of functional modelling and simulation is introduced. First, the necessity and the expected outcomes of the new concept are explained. Secondly, the methodology of functional modelling based on a modular concept and the basic elements are presented, with details of OFS (Organico Functional Set). Then, the implementation of the new modelling concept using Sherpa Engineering's PhiSim environment is described in order to perform simulations. Finally, the proposed modelling method is applied to two different applications: a generic parallel hybrid electric vehicle (HEV) and a waste water treatment unit of a building. Simulation results of parallel HEV application are also presented.

Abstract

This paper proposes a method for the combined estimation of the state of charge (SOC) and state of health (SOH) of batteries in hybrid and full electric vehicles. The technique is based on a set of five artificial neural networks that are used to tackle a regression and a classification task. In the method, the estimation of the SOC relies on the identification of the ageing of the battery and the estimation of the SOH depends on the behavior of the SOC in a recursive closed-loop. The networks are designed by means of training datasets collected during the experimental characterizations conducted in a laboratory environment. The lithium battery pack adopted during the study is designed to supply and store energy in a mild hybrid electric vehicle. The validation of the estimation method is performed by using real driving profiles acquired on-board of a vehicle. The obtained accuracy of the combined SOC and SOH estimator is around 97%, in line with the industrial requirements in the automotive sector. The promising results in terms of accuracy encourage to deepen the experimental validation with a deployment on a vehicle battery management system. Document type: Article

Abstract

In this paper TNO-Advance is presented. It is built in a modular way, therefore allowing quick assembling of specific vehicle configurations and easy integration of new component models and future evolutions of existing models. Its entensive library is built in Matlab/Simulink, taking advantage of its flexible and open architecture, the effective mathematical libraries and real-time application possibilities. TNO-Advance allows not only to develop, analyze and evaluate both chassis and powertrain systems, but also the interactions between them. All car suspensions can be represented and conventional as well as electric and hybrid electric vehicle powertrains. By applying the fast control options of Matlab/Simulink, chassis and powertrain controllers can be developed, as well as tested on robustness. Even interactions between vehiclesq, i.e. platooning, or new road transport systems, i.e. Intelligent Transport Systems and automatically guided vehicles, can be studied effectively.