Optimal power management framework for smart homes using electric vehicles and energy storage

2022 ◽  
Vol 134 ◽  
pp. 107358
Author(s):  
Ubaid ur Rehman ◽  
Kamran Yaqoob ◽  
Muhammad Adil Khan
Keyword(s):  
Energy Storage ◽  
Power Management ◽  
Electric Vehicles ◽  
Smart Homes ◽  
Management Framework ◽  
Optimal Power

Direct method for optimal power management in hybrid electric vehicles

2011 ◽  
Vol 12 (6) ◽  
pp. 943-950 ◽  
Author(s):  
R. Dosthosseini ◽  
A. Z. Kouzani ◽  
F. Sheikholeslam
Keyword(s):  
Power Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Direct Method ◽  
Optimal Power ◽  
Hybrid Electric

Observer-Based Power Management for Multi-Source Electric Vehicles Using Optimized Splitting Ratios

2018 ◽  
Author(s):  
Ahmed M. Ali ◽  
Dirk Söffker
Keyword(s):  
Power Conversion Efficiency ◽  
Real Time ◽  
Power Management ◽  
Conversion Efficiency ◽  
Electric Vehicles ◽  
Control Method ◽  
Power Conversion ◽  
Observer Design ◽  
Power Handling ◽  
Optimal Power

Optimal power management in real-time is a core technology of hybrid electric vehicles (HEVs). The online application of optimized power split ratios based on driver demand is a promising approach allowing near optimal power handling decisions in real-time. However, the fulfillment of exact power delivery (driveability) is an open challenge of this approach due to interpolation of driver’s demand to the optimized discrete solutions. Finding balanced power management that handles unscheduled loads and sustains required power conversion efficiency may significantly improve the experimental application of this approach. This work proposes an observer-based control method integrated to the power management system that ensures better driveability with minimal effect on power handling optimality. Modeling of traction system for observer design is based on a simplified brushless DC motor model. Identification of system parameters is achieved by a newly introduced error minimization algorithm using NSGA-II to obtain the same dynamic response as the original system. Results analysis shows 7% reduction of power consumption and 98% improvement of driveability at minimal mitigation of power conversion efficiency.

Tradeoffs between battery energy capacity and stochastic optimal power management in plug-in hybrid electric vehicles

2010 ◽  
Vol 195 (9) ◽  
pp. 2979-2988 ◽  
Author(s):  
Scott J. Moura ◽  
Duncan S. Callaway ◽  
Hosam K. Fathy ◽  
Jeffrey L. Stein
Keyword(s):  
Power Management ◽  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Energy Capacity ◽  
Optimal Power ◽  
Hybrid Electric ◽  
Battery Energy
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