(244f) Efficient Decision Making Based on a Hybrid Power Distribution Strategy - Application to a Fuel Cell Electric Vehicle
AIChE Annual Meeting
Monday, November 9, 2015 - 6:00pm to 8:00pm
This work presents a decision making methodology that determines the power sharing between two sources for the fulfilment of a single load demand. The field of energy management of hybrid energy systems is of increasing importance due to the necessity for optimum energy sharing between the various interconnected subsystems that either supply or demand energy and combined constitute an integrated system. The hybrid nature of such systems requires a well-designed energy management strategy (EMS) that determines how the demanded by the load power is distributed between the available energy sources while satisfying design and operation requirements.
The proposed approach is based on a hybrid timed automaton (HTA) which is used for the realization of an overall Energy Management Strategy (EMS) of the system. At hybrid powered systems discrete and continuous operating states coexist. The HTA switches between the system's operational modes and defines the set-points for the field-level control loops. More specifically the methodology implements an EMS which is applied to a fuel cell – battery system for vehicular applications. When a fuel cell is combined with a battery various decisions should be made in order for the integrated system to operate in an optimum way, while fulfilling the frequently and rapidly changing load demand. The objectives of the EMS are the fulfilment of the load demand, the optimal use of the available hydrogen, the protection of the battery’s lifetime and the preservation of the fuel cell’s integrity. The system consists of a lithium-ion battery stack, a Polymer Electrolyte Membrane (PEM) fuel cell and a DC load.
A set of operation scenarios are selected based on driving profiles and are used for the sensitivity analysis, the optimization problem and for the evaluation of the overall behaviour of the system. For each subsystem a model is used and a sensitivity analysis is performed that reveals the main parameters and variables that affect the response of the integrated system. An optimization problem is formulated that examines a set of operation scenarios included in the EMS. The objective of the optimization problem is to enhance the performance of the system. A number of alternatives for energy sharing will be presented that explore the effect that different priorities have for the energy supply subsystems. The potential of the proposed EMS will be demonstrated along with the response of the various subsystems and the integrated system.