Title :
Energy management in hybrid electric vehicles
Author :
Morchin, William C.
Author_Institution :
Electr. Bicycle Co., Auburn, WA, USA
fDate :
31 Oct-7 Nov 1998
Abstract :
A hybrid electric vehicle is propelled with stored energy from a battery or flywheel, plus energy produced by burning fuel in an engine. The cost of the energy consumed, as well as the quantity of air pollutants released, can be reduced by optimizing (1) the ratings of the battery and engine, and (2) the power output that will be delivered by each source under the expected driving conditions. Life-cycle cost can be minimized by running the engine at a constant speed and power, and by avoiding deep discharges of the battery. An on-board “energy manager, which contains an embedded computer, can track the energy content of the battery and optimize the load division between the battery and engine when given a travel time by the driver over a specified route. It can command the engine to deliver more power whenever the alternative is a life-shortening deep discharge of the battery. The vehicle designer needs to perform a system-engineering analysis to optimize the ratings of the engine and battery. For this he needs to understand the power required to move the vehicle at desired speeds over hills on the expected routes, and through headwinds that vary from day to day. In this supporting analysis we modeled the hybrid vehicle by using Lagrange´s calculus. We applied the model to a battery-powered electric bicycle which travelled a 200-mile route over a variety of hills. An unexpected result from this model is the energy consumed while travelling over a hilly route. With a specified travel time, no energy could be saved by climbing hills slowly and going down them rapidly. We did not consider the propulsion efficiency in this calculation. The next step will be to incorporate into the model variations in efficiency of the engine and the propulsion motor as speed is varied
Keywords :
electric vehicles; energy management systems; life cycle costing; systems engineering; Lagrange´s calculus; air pollutants; energy content; energy management; engine; expected driving conditions; hybrid electric vehicles; life-cycle cost; load division; power output; propulsion efficiency; propulsion motor; specified travel time; stored energy; system-engineering analysis; travel time; Air pollution; Batteries; Cost function; Energy management; Engines; Fault location; Flywheels; Fuels; Hybrid electric vehicles; Propulsion;
Conference_Titel :
Digital Avionics Systems Conference, 1998. Proceedings., 17th DASC. The AIAA/IEEE/SAE
Conference_Location :
Bellevue, WA
Print_ISBN :
0-7803-5086-3
DOI :
10.1109/DASC.1998.739880