Energy Management Strategies based on efficiency map for Fuel Cell Hybrid Vehicles

Abstract

The addition of a fast auxiliary power source like a supercapacitor bank in fuel cellbased vehicles has a great potential because permits a significant reduction of the hydrogen consumption and an improvement of the vehicle efficiency. The Energy Management Strategies, commanding the power split between the power sources in the hybrid arrangement to fulfil the power requirement, perform a fundamental role to achieve this objective. In this work, three strategies based on the knowledge of the fuel cell efficiency map are proposed. These strategies are attractive due to the relative simplicity of the real time implementation and the good performance. The strategies are tested both in a simulation environment and in an experimental setup using a 1.2-kW PEM fuel cell. The results, in terms of hydrogen consumption, are compared with an optimal case, which is assessed trough an advantageous technique also introduced in this work and with a pure fuel cell vehicle as well. This comparative reveals high efficiency and good performance, allowing to save up to 26% of hydrogen in urban scenarios.

Energy Management Strategy for a Bioethanol Isolated Hybrid System: Simulations and Experiments

“…with a P min f c = 300 W and a P max f c = 1200 W. In addition, the PEMFC power cannot be increased faster than a certain rise rate power (∆P max f c ) to avoid a lack of reactants and the power cannot be decreased faster than a certain fall rate power (∆P min f c ) to prevent overpressure in the PEMFC [29]. Therefore, the following constraints are added:…”

Analysis of Differential Flatness-Based Control for a Fuel Cell Hybrid Power Source

“…The energy management of multipower sources has been studied recently: for example, by Feroldi et al [38], who studied the control (based on the efficiency map) of a FC/supercapacitor hybrid power source for vehicle applications; by Jiang et al [39], who studied the control (based on adaptive control with statemachine estimation) of a FC/battery hybrid power source; by Li and Liu [40], who studied the control (using a fuzzy power control algorithm) of a FC/battery hybrid power source; and by Thounthong et al, whose work concerned a regulated dc-bus voltage FC/supercapacitor hybrid source (based on a basic linear controller operated by setting controller parameters that depend on a defined operating point) [16], a regulated dc-bus voltage FC/battery/supercapacitor hybrid source (based on a basic linear controller operated by setting controller parameters that depend on a defined operating point) [18] and an unregulated dc-bus voltage FC/battery hybrid source (based on the battery stateof-charge) [14]. Nevertheless, in these structures, there are still some aspects about the control laws that remain open to study, particularly in the area of dynamics, robustness, stability, and efficiency.…”

Parameters Optimization for Extended-range Electric Vehicle Based on Improved Chaotic Particle Swarm Optimization

“…At present, HEV's energy management control strategies mainly focus on the optimization-based strategy, including instantaneous optimization strategy and global optimization strategy [2]. However, in terms of practical engineering application, the rulebased energy management control strategies are more clear and easy to be implemented and developed.…”