Research on Air Mass Flow and Pressure Control Method for the Multi-Stack Fuel Cell System Based on Model Predictive Control Tongji University, School of Automotive Studies

Format:

Book

Conference/Event

Author/Creator:

Xie, Zhengchun, author.

Contributor:

Gao, Jianhua

Zhou, Su

Conference Name:

SAE 2023 Vehicle Powertrain Diversification Technology Forum (2023-08-26 : Shanghai, China)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2023

Summary:

The multi-stack fuel cell system (MFCS) has the advantages of higher efficiency, stronger robustness and longer life, and could be widely used in high-power application scenarios such as automobiles, airplanes, trains, and ships. The appropriate air mass flow and air pressure have a crucial impact on the output power performance indicators of the MFCS. Considering that the designed integrated air supply system for the MFCS has significant gas supply hysteresis and strong coupling between the inlet air mass flow and air pressure of each stack, this paper identifies multiple steady-state operating points of the fuel cell system to obtain corresponding linear predictive models and establishes corresponding predictive control algorithms. The Model Predictive Control (MPC) algorithms are switched in real-time based on the current load throughout the entire C-WTVC (China World Transient Vehicle Cycle) working condition. The simulation results show that the designed MPC algorithm can control all inlet air flow and air pressure of the MFCS (20kW/70kW/120kW) within the error range of ± 2% of the expected target values, which is significantly better than the PID control algorithm

Notes:

Vendor supplied data

Publisher Number:

2023-01-7037

Access Restriction:

Restricted for use by site license