<div class="section abstract"><div class="htmlview paragraph">In recent years, electrification of vehicle powertrains has become more mainstream to meet regulatory fuel economy and emissions requirements. Amongst the many challenges involved with powertrain electrification, developing supervisory controls and energy management of hybrid electric vehicle powertrains involves significant challenges due to multiple power sources involved. Optimizing energy management for a hybrid electric vehicle largely involves two sets of tasks: component level or low-level control task and supervisory level or high-level control task. In addition to complexity within powertrain controls, advanced driver assistance systems and the associated chassis controls are also continuing to become more complex. However, opportunities exist to optimize energy management when a cohesive interaction between chassis and powertrain controls can be realized. To optimize energy management along a given route, certain information such as the projected vehicle route, driver behavior, and battery charge level should be considered. In this paper, simulation models of a parallel P0/P4 hybrid electric vehicle are presented, which optimize powertrain controls using the Dynamic Programming approach. This virtual vehicle model is exercised through the HWFET and FTP-75 regulatory driving cycles to establish a performance baseline in a controlled driving environment. For comparison to off-cycle driving, the virtual vehicle is then also exercised through a real-world driving scenario over real-world roads, with similar trip characteristics to the regulatory tests, but with real traffic conditions during the day. This comparison provides insights into how optimized real-world fuel economy results can differ compared to the controlled testing environment, and how predictive powertrain controls can offer “in-situ” optimization of energy management.</div></div>

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Abstract:Military drive cycles typically consist of complex terrains, which include rough and deformable surfaces, steep grades, and sharp turns, which is a contrast to the commercial and passenger vehicle cycles. Typically, a one dimensional (1D) powertrain model is utilised to simulate and predict energy usage over a given drive cycle in GT-SUITE. This 1D model does not take into account lateral dynamics, short wavelength excitations, or tyre performance. These omissions are typically valid for straight line simple terrains where transient conditions are minimal. For complex terrains, such as the aforementioned military cycles, these assumptions are no longer valid and chassis dynamics need to be considered. This paper will demonstrate a transient powertrain dynamic model built in GT-SUITE and a comprehensive chassis dynamic model built in MSC.Adams/Car integrated through a co-simulation framework. It will include a detail analysis to describe the effects of the aforementioned phenomena on the vehicle performance. 90 D.M. Rizzo et al.Keywords: military; fuel economy; co-simulation.Reference to this paper should be made as follows: Rizzo, D.M., Kumaran, P., Zeman, J. and Jayakumar, P. (2017) 'Energy analysis of powertrain and chassis integrated simulation using a military duty cycle', Int.

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Abstract:Military drive cycles typically consist of complex terrains, which include rough and deformable surfaces, steep grades, and sharp turns, which is a contrast to the commercial and passenger vehicle cycles. Typically, a one dimensional (1D) powertrain model is utilised to simulate and predict energy usage over a given drive cycle in GT-SUITE. This 1D model does not take into account lateral dynamics, short wavelength excitations, or tyre performance. These omissions are typically valid for straight line simple terrains where transient conditions are minimal. For complex terrains, such as the aforementioned military cycles, these assumptions are no longer valid and chassis dynamics need to be considered. This paper will demonstrate a transient powertrain dynamic model built in GT-SUITE and a comprehensive chassis dynamic model built in MSC.Adams/Car integrated through a co-simulation framework. It will include a detail analysis to describe the effects of the aforementioned phenomena on the vehicle performance. 90 D.M. Rizzo et al.Keywords: military; fuel economy; co-simulation.Reference to this paper should be made as follows: Rizzo, D.M., Kumaran, P., Zeman, J. and Jayakumar, P. (2017) 'Energy analysis of powertrain and chassis integrated simulation using a military duty cycle', Int.