Abstract: The purpose of this article is to optimize the Equivalent Electric Circuit Model (EECM) of different orders to obtain greater precision in the modeling of Li-ion battery packs. Optimization includes considering circuits based on 1RC, 2RC and 3RC networks, with a dependent voltage source and a series resistor. The parameters are obtained experimentally using tests in the time domain and in the frequency domain. Due to the high non-linearity of the behavior of the battery pack, Genetic Algorithm (GA) was used to solve and optimize the parameters of each EECM considered (1RC, 2RC and 3RC). The objective of the estimation is to minimize the mean square error between the measured impedance in the real battery pack and those generated by the simulation of different proposed circuit models. The results have been verified by comparing the Nyquist graphs of the estimation of the complex impedance of the pack. As a result of the optimization, the 2RC and 3RC circuit alternatives are considered as viable to represent the battery behavior. These battery pack models are experimentally validated using a hardware-in-the-loop (HIL) simulation platform that reproduces the well-known New York City cycle (NYCC) and Federal Test Procedure (FTP) driving cycles for electric vehicles. The results show that using GA optimization allows obtaining EECs with 2RC or 3RC networks, with high precision to represent the dynamic behavior of a battery pack in vehicular applications.
Abstract: Modern day electric vehicles require compact high torque/power density motors for electric propulsion. This necessitates proper thermal management of the electric motors. The main focus of this paper is to compare the steady state thermal analysis of a conventional 20 kW 8/6 Switched Reluctance Motor (SRM) with that of an Induction Motor and Inset Permanent Magnet (IPM) motor of the same rating. The goal is to develop a proper thermal model of the three types of models for Finite Element Thermal Analysis. JMAG software is used for the development and simulation of the thermal models. The results show that the induction motor is subjected to more heating when used for electric vehicle application constantly, compared to the SRM and IPM.
Abstract: Batteries of electric vehicles (BEV) are becoming
more attractive with the advancement of new battery technologies
and promotion of electric vehicles. BEV batteries are recharged on
board vehicles using either the grid (G2V for Grid to Vehicle) or
renewable energies in a stand-alone application (H2V for Home to
Vehicle). This paper deals with the modeling, sizing and control of a
photovoltaic stand-alone application that can charge the BEV at
home. The modeling approach and developed mathematical models
describing the system components are detailed. Simulation and
experimental results are presented and commented.
Abstract: Electric vehicles are one of the most complicated
electric devices to simulate due to the significant number of different
processes involved in electrical structure of it. There are concurrent
processes of energy consumption and generation with different
onboard systems, which make simulation tasks more complicated to
perform. More accurate simulation on energy consumption can
provide a better understanding of all energy management for electric
transport. As a result of all those processes, electric transport can
allow for a more sustainable future and become more convenient in
relation to the distance range and recharging time. This paper
discusses the problems of energy consumption simulations for
electric vehicles using different software packages to provide ideas
on how to make this process more precise, which can help engineers
create better energy management strategies for electric vehicles.
Abstract: This paper mainly investigates the environmental and
economic impacts of worldwide use of electric vehicles. It can be
concluded that governments have good reason to promote the use of
electric vehicles. First, the global vehicles population is evaluated with
the help of grey forecasting model and the amount of oil saving is
estimated through approximate calculation. After that, based on the
game theory, the amount and types of electricity generation needed by
electronic vehicles are established. Finally, some conclusions on the
government-s attitudes are drawn.
Abstract: Electric vehicle (EV) is one of the effective solutions to
control emission of greenhouses gases in the world. It is of interest
for future transportation due to its sustainability and efficiency by
automotive manufacturers. Various electrical motors have been used
for propulsion system of electric vehicles in last decades. In this
paper brushed DC motor, Induction motor (IM), switched reluctance
motor (SRM) and brushless DC motor (BLDC) are simulated and
compared. BLDC motor is recommended for high performance
electric vehicles. PWM switching technique is implemented for speed
control of BLDC motor. Behavior of different modes of PWM speed
controller of BLDC motor are simulated in MATLAB/SIMULINK.
BLDC motor characteristics are compared and discussed for various
PWM switching modes under normal and inverter fault conditions.
Comparisons and discussions are verified through simulation results.
Abstract: This paper presents the development of a hybrid
thermal model for the EVO Electric AFM 140 Axial Flux Permanent
Magnet (AFPM) machine as used in hybrid and electric vehicles. The
adopted approach is based on a hybrid lumped parameter and finite
difference method. The proposed method divides each motor
component into regular elements which are connected together in a
thermal resistance network representing all the physical connections
in all three dimensions. The element shape and size are chosen
according to the component geometry to ensure consistency. The
fluid domain is lumped into one region with averaged heat transfer
parameters connecting it to the solid domain. Some model parameters
are obtained from Computation Fluid Dynamic (CFD) simulation and
empirical data. The hybrid thermal model is described by a set of
coupled linear first order differential equations which is discretised
and solved iteratively to obtain the temperature profile. The
computation involved is low and thus the model is suitable for
transient temperature predictions. The maximum error in temperature
prediction is 3.4% and the mean error is consistently lower than the
mean error due to uncertainty in measurements. The details of the
model development, temperature predictions and suggestions for
design improvements are presented in this paper.
Abstract: This paper describes the design considerations of an
experimental setup for research and exploring the drives of batteryfed
electric vehicles. Effective setup composition and its components
are discussed. With experimental setup described in this paper,
durability and functional tests can be procured to the customers.
Multiple experiments are performed in the form of steady-state
system exploring, acceleration programs, multi-step tests (speed
control, torque control), load collectives or close-to-reality driving
tests (driving simulation). Main focus of the functional testing is on
the measurements of power and energy efficiency and investigations
in driving simulation mode, which are used for application purposes.
In order to enable the examination of the drive trains beyond
standard modes of operation, different other parameters can be
studied also.