Abstract
Hybrid Electric Vehicles improve fuel economy by taking advantage of the Internal Combustion Engine (ICE) peak efficiency operating envelope and using an energy storage system to supply drive power when the ICE has lower efficiency. To achieve this, a hybrid design requires an ICE, a generator/motor, motor controllers, and an electric energy storage system (battery) which can be connected-up in a variety of ways such as, Parallel, and Series-Parallel configurations.Multiple strategies have been developed for hybrid electric vehicles energy management which make decisions based on inputs such as battery state of charge, driver torque demand, vehicle speed, and transmission gear. For example, as the state of charge of the battery decreases, it becomes more costly to use the electricity and hence the control system tends to transition the power source from battery to fuel.Although hybrid-electric haulage trucks have been implemented, energy storage has not been a feature of these systems. These trucks are typically arranged in Series configuration where the engine is completely decoupled from the wheels and used to provide electric power through a generator which powers electric motors on each of the wheels. The absence of a battery is an example of lost opportunity for fuel economy improvements through regenerative breaking and engine-off operation.This paper discusses the fuel economy question with respect to road geometry data and future speeds, a condition that can be determined for an autonomous haulage system with relative ease. Real-time access to such data can be put to advantage to maximize fuel economy. With a look-a-head system, even if the state of charge is low, the truck can continue to use the electric system if a downhill stretch is known to be ahead, so the system knows it can charge-up using regenerative breaking.
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