Multi-objective optimization of electric vehicle powertrain using scalable saturated motor model
Multi-objective optimization of electric vehicle powertrain using scalable saturated motor model
- New search for: Ramakrishnan, Kesavan
- New search for: Stipetic, Stjepan
- New search for: Gobbi, Massimiliano
- New search for: Mastinu, Gianpiero
- New search for: Ramakrishnan, Kesavan
- New search for: Stipetic, Stjepan
- New search for: Gobbi, Massimiliano
- New search for: Mastinu, Gianpiero
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.
Document information
Multi-objective optimization of electric vehicle powertrain using scalable saturated motor model
2016-04-01
1496702 byte
Conference paper
Electronic Resource
English
Similar titles
Multi-objective optimisation for battery electric vehicle powertrain topologies
| SAGE Publications | 2017
Multi-objective optimisation for battery electric vehicle powertrain topologies
| Online Contents | 2016
Multi-objective optimisation for battery electric vehicle powertrain topologies
| Online Contents | 2017