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Technical Paper

Realizing a Concept for High Efficiency and Excellent Driveability: The Downsized and Supercharged Hybrid Pneumatic Engine

2009-04-20
2009-01-1326
Pneumatic hybridization of internal combustion engines may prove to be a viable and cost-efficient alternative to electric hybridization. This paper evaluates the effects of pneumatic hybridization of various engine concepts using the criteria of fuel efficiency, driveability, emissions, and cost efficiency. The most promising engine concept is found to be the pneumatic hybridization combined with downsizing and supercharging spark-ignited engines. With this concept, a fuel consumption reduction of over 30% compared to a standard engine with the same rated power can be achieved. The poor driveability usually associated with heavily downsized and supercharged engines is completely overcome by injecting additional air during transients. The most important design issues for this new concept are discussed and several possible solutions are presented. Following these considerations, the first fully functional hybrid pneumatic engine was realized.
Technical Paper

Fuel-Optimal Power Split and Gear Selection Strategies for a Hybrid Electric Vehicle

2019-09-09
2019-24-0205
This paper presents a computationally inexpensive optimization algorithm to jointly compute the fuel-optimal state and input trajectories for the energy management of a hybrid electric vehicle (HEV) on a known driving mission. Specifically, we first introduce a model of the HEV that we leverage to formulate the fuel-optimal control problem as a mixed-integer convex program. Second, we use Pontryagin’s minimum principle and non-smooth convex analysis to derive the fuel-optimal control policy for the power split, the engine on/off decision, and the gear selection. Third, we combine the optimal control policy with single shooting and a bisection method to compute the optimal strategy for reaching a predefined terminal state of charge in the absence of path constraints. Fourth, we introduce a multi-point boundary value approach to deal with path constraints, thus obtaining the optimal control strategies for a complete driving cycle.
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