Optimization-based Energy Management Strategies Research Articles

Optimization-Based Energy Management Strategy for a 48-V Mild Parallel Hybrid Electric Power System

Abstract The application of a 48-V mild hybrid powertrain system is one of the eco-friendly technologies for global CO2 reduction in the present sector of hybrid electric vehicles (HEVs). It is well known that the energy management strategy is crucial for improving the fuel economy of the HEVs. Therefore, the strengths and the limitations of dynamic programming (DP) global optimization strategy and adaptive equivalent consumption minimization strategy (ECMS) for this kind of powertrain system under new European driving cycle (NEDC) and federal test procedure (FTP75) driving cycles are discussed in this paper. The results of the DP global optimization solution have also been adopted as a reference for evaluating the degree of optimality of real-time controllers. The reference start of charge (SOC) was found to be a very important parameter for the real-time ECMS approach. Thus, an adaptive ECMS approach using the SOC obtained from DP global optimization algorithm as a reference SOC in real-time ECMS control was studied. The study results in this paper may provide some theoretical support for future energy management optimization of a 48-V mild hybrid parallel powertrain system.

Optimization based energy management strategy for fuel cell/battery/ultracapacitor hybrid vehicle considering fuel economy and fuel cell lifespan

Optimization of energy management strategy (EMS) for fuel cell/battery/ultracapacitor hybrid electrical vehicle (FCHEV) is primarily aimed on reducing fuel consumption. However, serious power fluctuation has effect on the durability of fuel cell, which still remains one challenging barrier for FCHEVs. In this paper, we propose an optimized frequency decoupling EMS using fuzzy control method to extend fuel cell lifespan and improve fuel economy for FCHEV. In the proposed EMS, fuel cell, battery and ultracapacitor are employed to supply low, middle and high-frequency components of required power, respectively. For accurately adjusting membership functions of proposed fuzzy controllers, genetic algorithm (GA) is adopted to optimize them considering multiple constraints on fuel cell power fluctuation and hydrogen consumption. The proposed EMS is verified by Advisor-Simulink and experiment bench. Simulation and experimental results confirm that the proposed EMS can effectively reduce hydrogen consumption in three typical drive cycles, limit fuel cell power fluctuation within 300 W/s and thus extend fuel cell lifespan.

SOC Optimization Based Energy Management Strategy for Hybrid Energy Storage System in Vessel Integrated Power System

Hybrid energy storage system (HESS) consisted of battery and supercapacitor plays an essential role in supporting the normal operation of pulse load in vessel integrated power system (IPS) as well as improving power quality. However, due to the unique properties of the pulse load and diversified operations of the vessel, such advanced power system architectures tend to face greater challenges in optimal power allocation. In order to address the power allocation challenges, a novel optimized state-of-charge (SOC) feedback based energy management strategy is proposed for HESS in IPS to restrain the DC bus voltage fluctuation in this paper. Firstly, considering the operating characteristics of the pulse load in IPS, the optimized SOC of the HESS is introduced to the low-pass filter (LPF) with variable time constant to split the power in the HESS. Secondly, SOC recovery control of the supercapacitor is introduced to the LPF to optimize the size of the HESS as well as prolong the lifetime of the battery. Also, the enforced intervention is introduced to avoid the opposite state of the HESS. The proposed strategy can make full use of the HESS complementary characteristics to compensate the pulse load and optimize the HESS. Finally, the simulation conducted in PSCAD demonstrates the effectiveness of the strategy proposed in pulse load compensation as well as HESS optimization.

Optimization-based energy management strategy for a fuel cell/battery hybrid power system

This paper addresses the energy management strategy (EMS) for a fuel cell hybrid electric vehicle (FC-HEV). The purpose of this paper is to ensure an optimal power splitting between the fuel cell system (FCS) and the battery pack, taking into account the operating conditions of the FCS. The FCS is a multi-physics system, and consequently, its energetic performances depend on the operating conditions (i.e., temperature, gas relative humidity, gas stoichiometry, pressure and ageing). Specific techniques must be used to reach the best performances of the FCS. In this work, models are identified online by using the adaptive recursive least square (ARLS) method to seek a variation in the FCS performances. Then, an optimization algorithm is used on the updated model to find the best efficiency and power operating points. This process is used into an optimal EMS based on Pontryagin’s minimum principle, for a FC-HEV. The effectiveness of the proposed EMS is demonstrated by conducting studies on two FCSs with different levels of degradation.

Energy efficiency analysis of a series plug-in hybrid electric bus with different energy management strategies and battery sizes

This paper is concerned with the tank-to-wheel (TTW) analysis of a series plug-in hybrid electric bus operated in Gothenburg, Sweden. The bus line and the powertrain model are described. The definition and the calculation method of the recuperation and fuel-to-traction efficiencies are delineated for evaluating the TTW energy conversion. The two efficiencies are quantified and compared for two optimization-based energy management strategies, in which convex modeling and optimization are used. The impact of downsizing the battery on the two efficiencies is also investigated.