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The design and the supervision of hybrid electric vehicles (HEV) are strongly coupled. The mutual influence between the optimal components sizing and the optimal operating points choice makes the problem complex. This was previously exposed in literature for spark ignition (SI) HEV. In this paper, we address the same issue for diesel HEV. In this case, the energy management strategy must take nitrogen oxides (NOx) emissions into account in addition to fuel consumption. This paper presents an optimal supervision strategy and its impact on the electric components sizing. The energy management strategy is based on the equivalent consumption minimization strategy (ECMS) using Pontryagin's minimum principle. It allows an adjustable trade-off between NOx and fuel consumption to be minimized. It was validated experimentally with a hardware-in-the-loop test bed.

HCCI or CAI engine technologies require an accurate combustion monitoring and control because there is no direct ignition trigger. The control of ignition is inherently more difficult than in standard internal combustion engines and needs additional sensors such as cylinder pressure to perform closed loop combustion control. In this paper we present a rapid prototyping platform dedicated to high frequency recording and processing. We illustrate the functionalities of the platform through an example of combustion parameters estimation from indirect measurement (knock sensor). The paper ends with a comparison of direct and indirect combustion parameters computation in real time for closed loop combustion control purpose. The presented results are carried out with knock data series recorded on HCCI and CAI engines.

We propose a model based control strategy to adapt the injection settings according to the air path dynamics on a Diesel HCCI engine. This approach complements existing airpath and fuelpath controllers, and aims at accurately controlling the start of combustion. For that purpose, start of injection is adjusted based on a Knock Integral Model and intake manifold conditions. Experimental results are presented, which stress the relevance of the approach.

Among the last years, environmental concerns have raised the interest for biofuels. Ethanol, blended with gasoline seems particularly suited for the operation of internal combustion engines, and has been in use for severals years in some countries. However, it has a strong impact on engine performance, which is emphasized on recent engine architectures, with downsizing through turbocharging and variable valve actuation. Taking all the benefits of ethanol-blended fuel thus requires an adaptation of the engine management system. This paper intends to assess the effect of gasoline-ethanol blending from this point of view, then to describe a mean-value model of a fuel-flexible turbocharged PFI-SI engine, which will serve as a basis for the development of control algorithms. The focus will be in this paper on ethanol content estimation in the blend, supported by both simulation and experimental results.