Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 810243

Multi-Objective Optimization of Electric Vehicle Powertrain using Scalable Saturated Motor Model


Ramakrishnan, Kesavan; Stipetić, Stjepan; Gobbi, Massimiliano; Mastinu, Gianpiero
Multi-Objective Optimization of Electric Vehicle Powertrain using Scalable Saturated Motor Model // 2016 Eleventh International Conference on Ecological Vehicles and Renewable Energies (EVER) Proceedings
Monte Carlo, Monako, 2016. str. 1-6 doi:10.1109/EVER.2016.7476430 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 810243 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Multi-Objective Optimization of Electric Vehicle Powertrain using Scalable Saturated Motor Model

Autori
Ramakrishnan, Kesavan ; Stipetić, Stjepan ; Gobbi, Massimiliano ; Mastinu, Gianpiero

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
2016 Eleventh International Conference on Ecological Vehicles and Renewable Energies (EVER) Proceedings / - , 2016, 1-6

Skup
2016 Eleventh International Conference on Ecological Vehicles and Renewable Energies (EVER)

Mjesto i datum
Monte Carlo, Monako, 06.04.2016. - 08.04.2016

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Multi objective optimization ; Pareto-optimal set ; scaling laws ; saturated model

Sažetak
This paper presents a methodology for optimal sizing of the electric powertrain based on vehicle level objective functions. The design variables gear ratio, rated torque and rated speed of the motor are size dependant on the objective functions energy demand over a driving cycle, powertrain mass, and high speed gradeability. Multi-objective optimization handles these conflicting objective functions simultaneously and produces the Pareto-optimal solutions in both objective function and design variable domains. The novelty of the proposed approach is the utilization of analytical scalable saturated flux-linkage and loss motor model which is used for fast and accurate calculation of drive cycle energy consumption and motor mass. The concept is demonstrated on an example of in-wheel motor electric powertrain with four synchronous permanent magnet outer rotor machines.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Stjepan Stipetić (autor)

Poveznice na cjeloviti tekst rada:

Pristup cjelovitom tekstu rada doi ieeexplore.ieee.org

Citiraj ovu publikaciju:

Ramakrishnan, Kesavan; Stipetić, Stjepan; Gobbi, Massimiliano; Mastinu, Gianpiero
Multi-Objective Optimization of Electric Vehicle Powertrain using Scalable Saturated Motor Model // 2016 Eleventh International Conference on Ecological Vehicles and Renewable Energies (EVER) Proceedings
Monte Carlo, Monako, 2016. str. 1-6 doi:10.1109/EVER.2016.7476430 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Ramakrishnan, K., Stipetić, S., Gobbi, M. & Mastinu, G. (2016) Multi-Objective Optimization of Electric Vehicle Powertrain using Scalable Saturated Motor Model. U: 2016 Eleventh International Conference on Ecological Vehicles and Renewable Energies (EVER) Proceedings doi:10.1109/EVER.2016.7476430.
@article{article, author = {Ramakrishnan, Kesavan and Stipeti\'{c}, Stjepan and Gobbi, Massimiliano and Mastinu, Gianpiero}, year = {2016}, pages = {1-6}, DOI = {10.1109/EVER.2016.7476430}, keywords = {Multi objective optimization, Pareto-optimal set, scaling laws, saturated model}, doi = {10.1109/EVER.2016.7476430}, title = {Multi-Objective Optimization of Electric Vehicle Powertrain using Scalable Saturated Motor Model}, keyword = {Multi objective optimization, Pareto-optimal set, scaling laws, saturated model}, publisherplace = {Monte Carlo, Monako} }
@article{article, author = {Ramakrishnan, Kesavan and Stipeti\'{c}, Stjepan and Gobbi, Massimiliano and Mastinu, Gianpiero}, year = {2016}, pages = {1-6}, DOI = {10.1109/EVER.2016.7476430}, keywords = {Multi objective optimization, Pareto-optimal set, scaling laws, saturated model}, doi = {10.1109/EVER.2016.7476430}, title = {Multi-Objective Optimization of Electric Vehicle Powertrain using Scalable Saturated Motor Model}, keyword = {Multi objective optimization, Pareto-optimal set, scaling laws, saturated model}, publisherplace = {Monte Carlo, Monako} }

Citati:





    Contrast
    Increase Font
    Decrease Font
    Dyslexic Font