Fuel savings modeled for hybrid-electric front wheel loader

  • 12-Jan-2014 01:28 EST
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A parallel hybrid configuration was chosen for the research because using a series configuration would increase both the size and the maintenance of the machine.

Fuel efficiency and reduced emissions are two of the top considerations in all organic fuel power generation, including diesel engines. Alternative powertrain concepts including hybrid and fuel cell are being developed to address these considerations.

The concept behind hybrid devices is to store the excess (potentially wasted) mechanical energy in energy-storage devices and reuse that energy to support future operations. In any condition where the speed of motion is in opposite direction to the applied force or torque (e.g., vehicle braking or load movement by gravitation), the opportunity for regenerative energy recovery exists.

Objectives for a control strategy for hybrid-electric powertrain systems are to minimize fuel consumption while meeting low-emissions requirements; maintain or improve the work-machine productivity; and prevent the depletion of the energy-storage device.

University of Illinois-Chicago researchers developed a virtual model for a prototype machine that included the details of the machine dynamics. They selected as a prototype a medium wheel loader because of that type of machine’s functional versatility. C-language and embedded S-functions were used to develop a Simulink model.

A parallel hybrid configuration was chosen due to the fact that using a series configuration would increase both the size and the maintenance of the machine. The electric hybrid consists of a dual function motor/generator actuator; an inverter that requires a separate cooling system; and a lithium-ion battery pack. Battery sizing was done using standard logic based on the estimated power requirements and the desired performance. The diesel engine is the primary powerplant, while the electric hybrid acts as an energy booster.

The cycle model was built to mimic the commands of the real operator sent to the different machine systems as well as the work area: scooping up a pile of dirt, loading it into a truck or hopper, and returning to the pile.

The researchers developed a rule-based control strategy for ease of implementation in industry. Controller parameters were tuned to different cycles to minimize fuel consumption, bring the final battery charge level closest to the initial value, minimize cycle time, and regulate minimum engine speed to be close to 1000 rpm or higher.

Multiple factors were considered for the decision process, which are represented by parameters tuned for different cycles. The gain tuning process is an iterative and time-consuming process. The target from this process is to obtain an optimal set of parameters for robust design. The fractional factorial orthogonal array method is recommended for such a process since it optimizes the parameters and allows for the study of interactions between them.

The results obtained showed that when the engine is downsized and the hybrid system is implemented, the engine achieves more fuel savings than with the original engine. The disadvantage of using a downsized engine is that if the battery runs out of charge, the engine may not be able to support machine functions. On the other hand, the hybrid with the original engine doesn’t provide the desired fuel-consumption reduction.

The implementation of a hybrid system on a medium wheel loader is expected to maintain the productivity of the machine within acceptable range. The use of the hybrid system with a 7-L engine is expected to reduce the fuel consumption compared to the baseline machine by 20-27% at the simulated cycles. The use of the hybrid system with a 9-L engine is expected to reduce fuel consumption compared to the baseline machine by 6-7% at the simulated cycles.

The hybrid system supplies 14-17% of the torque required by the machine during its work cycle.

This article is based on SAE International technical papers 2013-01-2395 and 2013-01-2396 by Mohamed H. Zaher and Sabri Cetinkunt of the University of Illinois-Chicago.

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