Online energy management for hybrid electric vehicles

Hybrid electric vehicles (HEVs) are equipped with multiple power sources for improving the efficiency and performance of their power supply system. An energy management (EM) strategy is needed to optimize the internal power flows and satisfy the driver's power demand. To achieve maximum fuel profits from EM, many solution methods have been presented. Optimal solution methods are typically not feasible in an online application due to their computational demand and their need to have a priori knowledge about future vehicle power demand. In this paper, an online EM strategy is presented with the ability to mimic the optimal solution but without using a priori road information. Rather than solving a mathematical optimization problem, the methodology concentrates on a physical explanation about when to produce, consume, and store electric power. This immediately reveals the vehicle characteristics that are important for EM. It is shown that this concept applies to many existing HEVs as well as possible future vehicle configurations. Since the method only focuses on typical vehicle characteristics, the underlying algorithm requires minor computational effort and can be executed in real time. Clear directions for online implementation are given in this paper. A parallel HEV with a 5-kW integrated starter/generator (ISG) is selected to demonstrate the performance of the EM strategy. Simulation results indicate that the proposed EM strategy exhibits similar behavior as an optimal solution obtained from dynamic programming. Profits in fuel economy primarily arise from engine stop/start and energy obtained during regenerative braking. This latter energy is preferably used for pure electric propulsion where the internal combustion engine is switched off

Fuel reduction potential of energy management for vehicular electric power systems

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

Energy management for vehicle power net with flexible electric load demand

The electric power demand in road vehicles increases rapidly and to supply all electric loads efficiently, energy management (EM) turns out to be a necessity. In general, EM exploits the storage capacity of a buffer connected to the vehicle's power net, such that energy is stored or retrieved at moments that the production of electric power is relative cheap or expensive, respectively. This paper adds an extra degree of freedom, by considering electric loads with a flexible power demand. A strategy based on optimization techniques as well as a rule-based strategy are developed. Simulations illustrate the benefits of applying these flexible loads, as they offer more freedom for EM and moreover, reduce the activity of the storage buffer significantl

Energy management strategies for vehicle power nets

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 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