Anti-idling systems for service vehicles: Modeling and experiments

Abstract

Vehicles are a major source of fuel consumption and air pollution. Any improvement in their efficiency impacts the environment and economy positively. Service vehicles such as food delivery trucks have many loading and unloading stops during their daily work cycle. In these stops, their auxiliary devices need to be active and hence the engines run at its idling speed resulting in extremely low fuel efficiency. A regenerative auxiliary power system is proposed for anti-idling of service vehicles. This system reduces the engine idling and maximizes the regenerative braking energy by utilizing an additional battery. In this paper, different system configurations and possible options for integration of regenerative auxiliary power system to the vehicle powertrain are studied. Backward-looking scalable powertrain components modeling approach is utilized to create a flexible system model which can be easily modified for different vehicles. The full system model has scalability and composability features. A library for common components used in service vehicles is developed for ease of development of such anti-idling systems. Hardware-in-the-loop tests and a prototype model of regenerative auxiliary power system have been utilized for the laboratory evaluation in order to validate the model and characterize the regenerative auxiliary power system components.

Design of a Regenerative Auxiliary Power System for Service Vehicles

“…In this research, our target vehicle is the GMC Savana 2500, whose specifications are given in the literature [14]. To study the vehicle's fuel economy, a drive cycle is created by combining several standard drive cycles as shown in Table 1 and Fig.…”

“…In this study, a backward-looking modeling approach is used to reduce the unnecessary dynamic details of the components and vehicle system, which leads to less computational time. The detailed modeling process of the RAPS components has been presented in the literature [14].…”

“…For the optimal RAPS, the initial investment will be returned after 2-3 years, which is half the expected lifetime of the batteries. Further information is provided in the literature [14].…”