Design and simulation of an optimal energy management strategy for plug-In electric vehicles

Name: Design and simulation of an optimal energy management strategy for plug-In electric vehicles
Author: Gözüküçük, M. A., Akdoğan, Taylan, Hussain, Waqas, Tasooji, Tohid Kargar, Şahin, Mert, Çelik, M., Uğurdağ, Hasan Fatih

İsim	Design and simulation of an optimal energy management strategy for plug-In electric vehicles
Yazar	Gözüküçük, M. A., Akdoğan, Taylan, Hussain, Waqas, Tasooji, Tohid Kargar, Şahin, Mert, Çelik, M., Uğurdağ, Hasan Fatih
Basım Tarihi:	2018
Basım Yeri	- IEEE
Konu	Application software, Electric vehicles, Embedded software, Energy management, Monte Carlo method, Torque control, Speed control
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-1-5386-7641-7
Kayıt Numarası	532054d4-597e-4759-ad48-2bc55263884c
Lokasyon	Natural and Mathematical Sciences, Electrical & Electronics Engineering
Tarih	2018
Notlar	TÜBİTAK
Örnek Metin	Energy management algorithms play a critical role in improving the energy efficiency of modern electric vehicles. In order to be desirable for the customer, electric vehicles should be capable of long distance driving on a single battery charge with a range which must be comparable to the values of their conventional counterparts. To achieve this goal, both the use of large-capacity battery and the development of a custom energy management algorithm are necessary. Thus, one must solve equations of vehicle dynamics, which is a part of conventional methods used in generalized energy management problems. In this paper, a Monte Carlo method is proposed for probabilistic prediction of the optimum energy to attain a given route. The route in question is obtained from the Google Maps and includes locations and road topologies. First, optimum speed set-points are generated for each state of the journey, and this generated speed array is imported into the vehicle control system to generate the required torque for vehicle propulsion. Then, this process is repeated with a constant average speed for comparison purposes. The simulation results show that an electric vehicle gains significant energy efficiency over a Hardware in the Loop (HIL) emulation, when it is being controlled with the proposed speed set-points generated by the Monte Carlo method.
DOI	10.1109/CEIT.2018.8751923

Kaynağa git Özyeğin Üniversitesi

Aramaya Dön

Özyeğin Üniversitesi

Kaynağa git

Design and simulation of an optimal energy management strategy for plug-In electric vehicles

Yazar Gözüküçük, M. A., Akdoğan, Taylan, Hussain, Waqas, Tasooji, Tohid Kargar, Şahin, Mert, Çelik, M., Uğurdağ, Hasan Fatih

Basım Tarihi 2018

Basım Yeri - IEEE

Konu Application software, Electric vehicles, Embedded software, Energy management, Monte Carlo method, Torque control, Speed control

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-1-5386-7641-7

Kayıt Numarası 532054d4-597e-4759-ad48-2bc55263884c

Lokasyon Natural and Mathematical Sciences, Electrical & Electronics Engineering

Tarih 2018

Notlar TÜBİTAK

Örnek Metin Energy management algorithms play a critical role in improving the energy efficiency of modern electric vehicles. In order to be desirable for the customer, electric vehicles should be capable of long distance driving on a single battery charge with a range which must be comparable to the values of their conventional counterparts. To achieve this goal, both the use of large-capacity battery and the development of a custom energy management algorithm are necessary. Thus, one must solve equations of vehicle dynamics, which is a part of conventional methods used in generalized energy management problems. In this paper, a Monte Carlo method is proposed for probabilistic prediction of the optimum energy to attain a given route. The route in question is obtained from the Google Maps and includes locations and road topologies. First, optimum speed set-points are generated for each state of the journey, and this generated speed array is imported into the vehicle control system to generate the required torque for vehicle propulsion. Then, this process is repeated with a constant average speed for comparison purposes. The simulation results show that an electric vehicle gains significant energy efficiency over a Hardware in the Loop (HIL) emulation, when it is being controlled with the proposed speed set-points generated by the Monte Carlo method.

DOI 10.1109/CEIT.2018.8751923