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In [1] a new concept was developed for the design of hybrid electric powertrains that includes optimization of the component sizes as well as control strategies. In contrast to most existing publications, the approach explicitly considers the conflicting goals of low fuel consumption and high vehicle longitudinal dynamics and the trade-off is quantified. This is achieved by formulating two multiobjective...
Improved fuel consumption and lower emissions are two of the key objectives for future transportation. Hybrid electric vehicles (HEVs), in which two or more power systems are combined, can meet these objectives through the capture and reuse of regenerated braking energy and through optimized use of the prime mover. However, more complicated power-management strategies are required for such vehicles...
Air-ratio relates closely to pollution reduction, fuel efficiency and driveability among all of the engine control variables. Maintaining the air-ratio to be the stoichiometric value can obtain the best balance between power output and fuel consumption. The paper presents a nonlinear model predictive control algorithm for air-ratio regulation based on online neural network. The control algorithm has...
The European standards concerning the pollutants emissions of automotive engine become more and more severe. Modern automotive engines are equipped with an increasing number of new technologies and controlling elements. The consequence of this evolution, is the increase of the number of the controllable parameters, the difficulty to understand the engine behavior, and to find the parameters settings...
To comprehensively deal with tracking capability and fuel economy issue of ACC-activated vehicle, this paper presents a MPC based vehicular following control algorithm. After compensating the nonlinearity of vehicle longitudinal dynamics by inverse model, the car-following system is built as 3-state space linear model. On its basis, a standard MPC optimization cost is constructed mainly considering...
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