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ASIL decomposition is a method described in the ISO 26262 standard for the assignment of ASILs to redundant requirements. Although ASIL decomposition appears to have similar intent to the hardware fault tolerance concept of IEC 61508-2, ASIL decomposition is not intended to reduce ASIL assignments to hardware elements for random hardware failures, but instead focuses on functions and requirements in the context of systematic failures. Based on our participation in the development of the standard, the method has been applied in different ways in practice, not all of which are fully consistent with the intent of the standard. Two potential reasons that may result in the use of “modified” ASIL algebra include the need of OEMs to partition a system and specify subsystem requirements to suppliers and the need for designers to construct systems bottom up.

The two-mode hybrid system has several advantages over a one-mode EVT system: greater ability to transmit power mechanically and minimize electrical recirculation power, maximize fuel economy improvement and best meet demanding vehicle requirements. Extending the two-mode hybrid electric vehicle (HEV) to two-mode plug-in hybrid electric vehicle (PHEV) is significant not only to make the internal combustion engine (ICE)-based vehicle cleaner and more efficient in the near term, but also to provide a potential path to battery electric vehicles in the future. For PHEV, the enhanced electric drive capability is of vital importance to achieve best efficiency and best electric only performance. This paper describes the development of a prototype two-mode hybrid powertrain with enhanced EV capability (2MH4EV). The prototype drive unit includes an additional input brake to the existing General Motors FWD 2-mode HEV system.

This research investigates the energy savings achieved through eco-driving controls in connected and automated vehicles (CAVs), with a specific focus on the influence of powertrain characteristics. Eco-driving strategies have emerged as a promising approach to enhance efficiency and reduce environmental impact in CAVs. However, uncertainty remains about how the optimal strategy developed for a specific CAV applies to CAVs with different powertrain technologies, particularly concerning energy aspects. To address this gap, on-track demonstrations were conducted using a Chrysler Pacifica CAV equipped with an internal combustion engine (ICE), advanced sensors, and vehicle-to-infrastructure (V2I) communication systems, compared with another CAV, a previously studied Chevrolet Bolt electric vehicle (EV) equipped with an electric motor and battery.

This paper presents a methodology to optimize the blending of charge-depleting (CD) and charge-sustaining (CS) modes in a multi-mode plug-in hybrid electric vehicle (PHEV). The objective of the optimization is to best utilize onboard energy for minimum overall energy consumption based on speed and elevation profile. The optimization reduces overall energy consumption when the selected route cannot be completely driven in all-electric mode. The optimization method splits drive cycles into constant distance segments and then uses a reduced-order model to sort the segments by the best use of battery energy vs. fuel energy. The PHEV used in this investigation is the Stellantis Pacifica. Results support energy savings up to 20% which depend on the route and initial battery State of Charge (SOC). Initial optimization takes 1 second for 38 km and 3 seconds for 154 km.