This paper presents a critical review of the drivelines in all-electric vehicles (EVs). The motor topologies that are the best candidates to be used in EVs are presented. The advantages and disadvantages of each electric motor type are discussed from a system perspective. A survey of the electric motors used in commercial EVs is presented. The survey shows that car manufacturers are very conservative when it comes to introducing new technologies. Most of the EVs on the market mount a single induction or permanent-magnet (PM) motor with a traditional mechanic driveline with a differential. This paper illustrates that comparisons between the different motors are difficult by the large number of parameters and the lack of a recommended test scheme. The authors propose that a standardized drive cycle be used to test and compare motors.

/pdf/electrical-motor-drivelines-in-commercial-all-electric-1ho8rutglq.pdf

Electrical Motor Drivelines in Commercial All-Electric Vehicles: A Review

An Internet of Energy Things Based on Wireless LPWAN

With its popularisation, electric vehicle (EV) has been part of the important load of smart grid. The analysis on charging demands of EVs is the basis of the study of influences on power grid and charging infrastructures planning. Charging demand calculation is based on the precise analysis on the driving law of users. This study proposes a method based on the stochastic simulation of trip chain to solve the existing problem. First, the concept and characteristic variables (trip start time, driving time, parking duration, driving distance and trip purpose) of trip chain are introduced. Second, the probability distribution models of these variables are established considering their correlative relationships. Third, using Monte Carlo method, the complete trip chains are simulated, and then the spatial–temporal distributions of charging demands are calculated. Finally, based on the National household trip survey data, and according to the proposed method, charging demands in different areas are studied. The results show that the proposed method can accurately simulate the driving law of users and reflect spatial–temporal distribution characteristics of charging demands, and different charging scenarios will lead to different forms of charging demand distribution, which will exert different impacts on power system.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-gtd.2015.0995

Charging demand for electric vehicle based on stochastic analysis of trip chain

We present a sensitivity analysis for a mechanical model, which is used to estimate the energy demand of battery electric vehicles. This model is frequently used in literature, but its parameters are often chosen incautiously, which can lead to inaccurate energy demand estimates. We provide a novel prioritization of parameters and quantify their impact on the accuracy of the energy demand estimation, to enable better decision making during the model parameter selection phase. We furthermore determine a subset of parameters, which has to be defined, in order to achieve a desired estimation accuracy. The analysis is based on recorded GPS tracks of a battery electric vehicle under various driving conditions, but results are equally applicable for other BEVs. Results show that the uncertainty of vehicle efficiency and rolling friction coefficient have the highest impact on accuracy. The uncertainty of power demand for heating and cooling the vehicle also strongly affects the estimation accuracy, but only at low speeds. We also analyze the energy shares related to each model component including acceleration, air drag, rolling and grade resistance and auxiliary energy demand. Our work shows that, while some components make up a large share of the overall energy demand, the uncertainty of parameters related to these components does not affect the accuracy of energy demand estimation significantly. This work thus provides guidance for implementing and calibrating an energy demand estimation based on a longitudinal dynamics model.

Sensitivity analysis for energy demand estimation of electric vehicles

The first commercially available plug-in hybrid electric vehicle (PHEV), the General Motors (GM) Volt, was introduced into the market in mid-December 2010. The Volt uses a series-split powertrain architecture, which provides benefits over the series architecture that typically has been considered for use in electric-range extended vehicles (EREVs). A specialized EREV powertrain, called the Voltec, drives the Volt through its entire range of speed and acceleration with battery power alone and within the limit of battery energy, thereby displacing more fuel with electricity than a PHEV, which characteristically blends electric and engine power together during driving. This paper assesses the benefits and drawbacks of these two different plug-in hybrid electric architectures (series versus series-split) by comparing component sizes, system efficiency, and fuel consumption over urban and highway drive cycles. Based on dynamic models, a detailed component control algorithm was developed for each PHEV. In particular, for the GM Voltec, a control algorithm was proposed for both electric machines to achieve optimal engine operation. The powertrain components were sized to meet all-electric-range, performance, and grade capacity requirements. This paper presents and compares the impact of these two different powertrain configurations on component size and fuel consumption.

https://www.autonomie.net/docs/5%20-%20Presentations/powertrain/SAE%202012-01-1027.pdf

Comparison of Powertrain Configuration for Plug-in HEVs from a Fuel Economy Perspective

A vehicle is consider Green when it more environmentally friendly than the traditional petroleum combustion engine, in which includes any nontraditional vehicle like, HEV, Plug In, EV, Fuel Cell, Bio fuel etc. that improves fuel economy. The development of electric vehicle has been over a hundred years but failure to gain the public acceptance in various stages due to various reasons which explained. While EV was never mass produced, Hybrid electric vehicle gains the momentum in recent years. Ford has launched its second generation of HEV and GM also announced the debut of the Volt in 2010. Comparing to the regular HEV, Plug in is the new trend in hybrid auto development due to extend travel range in electrical mode and a possibility of a zero emission as long as travel distance is less than charging threshold. However, more recently, an electrification trend in automotive industry has been evolved and will revolutionize the industry. With the correct policy and government help and advancement of electric vehicle technology, the prospect of Electric Vehicle will be bright and the focus point of future development.

Lixin Situ

Papers

Electric Vehicle development: The past, present & future