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Connected and automated vehicles (CAVs) have the potential to eliminate road vehicle collisions and other traffic incidences. Whilst the main motivation for the introduction of vehicular communication systems is to improve safety, they also provide opportunities to reduce CO2 and other harmful pollutant emissions as well as transportation energy costs. Vehicle communication link with other automobiles and Intelligent Transportation Systems (ITS), when combined with the use of on-board high definition navigation maps, enable the vehicle control systems to optimize their operation and streamline traffic flow. This paper presents the development and evaluation of proof of concept control algorithms which optimize the vehicle’s propulsive energy consumption. Consideration is also given to journey time and other drivability and autonomous driving attributes and constraints.

Fuel cell hybrid systems have emerged rapidly in efforts to reduce emissions. The success of these systems mainly depends on implementation of suitable control architectures. This paper presents a control system design for a novel fuel cell - IC Engine hybrid power system. Control oriented models of the system components are developed and integrated. Based on the simulation results of the system model, the control variables are identified. The main objective for the control design is to manage fuel, air and exhaust flows in a way to deliver the required load on the system within local constraints. The controller developed for regulating flows in the system is based on model predictive control theory. The performance of the overall control system is assessed through simulations on a nonlinear dynamic model.

This paper presents a control system design strategy for a novel fuel cell - internal combustion engine hybrid power system. Dynamic control oriented models of the system components are developed. The transient behavior of the system components is investigated in order to determine control parameters and set-points. The analysis presented here is the first step towards development of a controller for this complex system. The results indicate various possibilities for control design and development. A control strategy is discussed to achieve system performance optimization.