Intelligent Energy Distribution for Series HEVs Using Determined Optimal Driving Patterns via a Genetic Algorithm 2013-01-0572
This paper introduces an intelligent energy distribution scheme for series plug-in hybrid electric vehicles (PHEVs) which incorporates the complexity of human driving behavior. Driving styles can have a significant impact on fuel consumption, but it is often unclear how one should drive to get the optimal fuel efficiency. Hybrid electric vehicles have been shown to improve fuel economy, reduce vehicle emissions and maintain drivability by incorporating electric motors into the drivetrain. Due to the highly complex system design and vehicle architecture, sophisticated energy management strategies (EMS) are required to optimize the vehicle performance. Currently, the power management system is based on static thresholds optimized on a fixed drive cycle for a given vehicle. This paper introduces an adaptive control method for EMS utilizing the complexity of human driving patterns for energy distribution in a series PHEV. By utilizing the Genetic Algorithm (GA) optimization method to determine the optimal driving patterns offline, an optimal EMS can be derived to maintain an effective control algorithm in real-time.
Citation: Ho, P. and Klang, E., "Intelligent Energy Distribution for Series HEVs Using Determined Optimal Driving Patterns via a Genetic Algorithm," SAE Technical Paper 2013-01-0572, 2013, https://doi.org/10.4271/2013-01-0572. Download Citation
Author(s):
Phu Ho, Eric Klang
Affiliated:
North Carolina State University
Pages: 6
Event:
SAE 2013 World Congress & Exhibition
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Hybrid electric vehicles
Electric motors
Fuel economy
Fuel consumption
Adaptive control
Energy conservation
Vehicle performance
Mathematical models
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