2014
DOI: 10.4028/www.scientific.net/amr.926-930.1387
|View full text |Cite
|
Sign up to set email alerts
|

Parameter Matching and Simulation Study of Powertrain for Extended-Range Electric Vehicle

Abstract: A method of parameter matching for extended-range electric vehicle (E-REV) was discussed to meet the requirements given, then using a model and genetic algorithm to optimize the transmission ratio of E-REV. The parameters of the battery and range extender (RE) are designed by driving range and power requirement. The simulation results shows that the parameter matching is reasonable, and the power performance and driving range could meet the design requirements.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2018
2018
2021
2021

Publication Types

Select...
1
1

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 2 publications
0
1
0
Order By: Relevance
“…An APU control method based on linear variable parameters and robust controllers is proposed in [24], which realizes the stable control of APU output voltage and is composed of a diesel engine and three-phase uncontrolled rectifier, effectively restraining the load mutation to the engine speed and the influence of current generation. A distributed power design was proposed, and the powertrain parameters of this design were calculated in [25,26]. Most methods concentrate on energy management strategy optimization and improvement for APU fuel economy [27].…”
Section: Introductionmentioning
confidence: 99%
“…An APU control method based on linear variable parameters and robust controllers is proposed in [24], which realizes the stable control of APU output voltage and is composed of a diesel engine and three-phase uncontrolled rectifier, effectively restraining the load mutation to the engine speed and the influence of current generation. A distributed power design was proposed, and the powertrain parameters of this design were calculated in [25,26]. Most methods concentrate on energy management strategy optimization and improvement for APU fuel economy [27].…”
Section: Introductionmentioning
confidence: 99%