This paper presents a novel method to solve the energy management problem for hybrid electric vehicles (HEVs) with engine start and gearshift costs. The method is based on a combination of deterministic dynamic programming (DP) and convex optimization. As demonstrated in a case study, the method yields globally optimal results while returning the solution in much less time than the conventional DP method. In addition, the proposed method handles state constraints, which allows for the application to scenarios where the battery state of charge (SOC) reaches its boundaries.

Motivated by the fact that the real driving NOx emissions (RDE) of conventional diesel vehicles can exceed the legislation norms by far, a concept for the control of RDE with a diesel parallel hybrid electric vehicle (HEV) is proposed. By extending the well-known equivalent consumption minimization strategy (ECMS), the power split degree of freedom is used to control the NOx emissions and the battery state of charge (SOC) simultaneously. Through an appropriate formulation of the problem, the feedback control is shown to be separable into two dependent PI controllers. By hardware-in-the-loop (HIL) experiments, as well as by simulations, the proposed method is shown to minimize the fuel consumption while tracking a given reference trajectory for both the NOx emissions and the battery SOC.

The optimal sizing and control of a hybrid tracked vehicle is presented and solved in this paper. A driving schedule obtained from field tests is used to represent typical tracked vehicle operations. Dynamics of the diesel engine-permanent magnetic AC synchronous generator set, the lithium-ion battery pack, and the power split between them are modeled and validated through experiments. Two coupled optimizations, one for the plant parameters, forming the outer optimization loop and one for the control strategy, forming the inner optimization loop, are used to achieve minimum fuel consumption under the selected driving schedule. The dynamic programming technique is applied to find the optimal controller in the inner loop while the component parameters are optimized iteratively in the outer loop. The results are analyzed, and the relationship between the key parameters is observed to keep the optimal sizing and control simultaneously.

In response to the increasingly stringent emission regulations and a demand for ever lower fuel consumption, diesel engines have become complex systems. The exploitation of any leftover potential during transient operation is crucial. However, even an experienced calibration engineer cannot conceive all the dynamic cross couplings between the many actuators. Therefore, a highly iterative procedure is required to obtain a single engine calibration, which in turn causes a high demand for test‐bench time. Physics‐based mathematical models and a dynamic optimisation are the tools to alleviate this dilemma. This paper presents the methods required to implement such an approach. The optimisation‐oriented modelling of diesel engines is summarised, and the numerical methods required to solve the corresponding large‐scale optimal control problems are presented. The resulting optimal control input trajectories over long driving profiles are shown to provide enough information to allow conclusions to be drawn for causal control strategies. Ways of utilising this data are illustrated, which indicate that a fully automated dynamic calibration of the engine control unit is conceivable. An experimental validation demonstrates the meaningfulness of these results. The measurement results show that the optimisation predicts the reduction of the fuel consumption and the cumulative pollutant emissions with a relative error of around 10% on highly transient driving cycles.

In this paper we demonstrate the potential of combining electric hybridization with a dual-fuel natural gas-Diesel engine. We show that carbon dioxide emissions can be reduced to 43 gram per kilometer with a subcompact car on the New European Driving Cycle (NEDC). The vehicle is operated in charge-sustaining mode, which means that all energy is provided by the fuel. The result is obtained by hardware-in-the-loop experiments where the engine is operated on a test bench while the rest of the powertrain as well as the vehicle are simulated. By static engine measurements we demonstrate that the natural gas-Diesel engine reaches efficiencies of up to 39.5%. The engine is operated lean at low loads with low engine out nitrogen oxide emissions such that no nitrogen oxide aftertreatment is necessary. At medium to high loads the engine is operated stoichiometrically, which enables the use of a cost-efficient three-way catalytic converter. By vehicle emulation of a non-hybrid vehicle on the Worldwide harmonized Light vehicles Test Procedure (WLTP), we demonstrate that transient operation of the natural gas-Diesel engine is also possible, thus enabling a non-hybridized powertrain as well.