Abstract-In the near future, a significant increase in electric power consumption in vehicles is expected. To limit the associated increase in fuel consumption and exhaust emissions, smart strategies for the generation, storage/retrieval, distribution, and consumption of electric power will be used. Inspired by the research on energy management for hybrid electric vehicles (HEVs), this paper presents an extensive study on controlling the vehicular electric power system to reduce the fuel use and emissions, by generating and storing electrical energy only at the most suitable moments. For this purpose, both off-line optimization methods using knowledge of the driving pattern and on-line implementable ones are developed and tested in a simulation environment. Results show a reduction in fuel use of 2%, even without a prediction of the driving cycle being used. Simultaneously, even larger reductions of the emissions are obtained. The strategies can also be applied to a mild HEV with an integrated starter alternator (ISA), without modifications, or to other types of HEVs with slight changes in the formulation.Index Terms-Energy management, fuel reduction, hybrid electric vehicles (HEVs), regenerative braking, vehicular electric power system.

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The electric power demand in road vehicles increases rapidly. Energy management (EM) turns out to be a viable solution for supplying all electric loads efficiently. The EM strategies developed in this paper focus on vehicles with a conventional drivetrain. By exploiting the storage capacity of the battery, the production, and distribution of electric power is rescheduled to more economic moments. In addition, this paper explores the advantages of electric loads with a flexible power demand. Based on optimization techniques, an optimal offline strategy as well as a causal online strategy are presented. Simulations illustrate the benefits of the EM strategies in terms of fuel economy. The online strategy has also been implemented in a series-production vehicle. Real-world experiments on a roller dynamometer test-bench validate the strategy, but also reveal additional fuel benefits due to unexpected side-effects from the engine control unit and the driver. Measured profits in fuel economy are as large as 2.6%, with only minimal changes to the vehicle hardware.Index Terms-Energy management, flexible electric loads, fuel optimal control, road vehicle power systems.

In the near future a significant increase in electric power consumption in vehicles is to he expected. To limit the associated increase in fuel consumption and exhaust emissions, smart strategies for the generation, storagdretrieval, distribution, and consumption of the electric power can he used. This paper presents a case study on controlling the vehicle power net using knowledge of the driving pattern to minimize fuel use, by generating and storing extra energy only at the most suitable moments. For this purpose, both off-line and online optimization methods are developed and tested in a simulation environment. Results show a reduction in fuel use, even without an accurate prediction of the drive cycle.

In the near future a significant increase in electric power consumption in vehicles is to be expected. To limit the associated increase in fuel consumption and exhaust emissions, smart strategies for the generation, storage/retrieval, distribution and consumption of the electric power can be used. This paper considers a vehicle configuration with a conventional drive train. Two energy management strategies that control the alternator power are analysed: a regenerative braking strategy and a more advanced strategy based on optimisation techniques. The potential behind these strategies is analysed by studying the typical characteristics of components that are directly related to the energy flow in the vehicle. It is shown that operating the internal combustion engine at the highest efficiency will not inherently lead to the lowest fuel consumption. Subsequently, engineering rules are presented to evaluate the performance that can be expected for each strategy. The component characteristics are included as input parameters to make the method generally applicable. To show the value of the engineering rules, the potential fuel reduction is computed for a specific vehicle configuration and driving cycle and compared with simulations results.