Current Management in a Hybrid Fuel Cell Power System: A Model-Predictive Control Approach

By Ardalan Vahidi, Anna G. Stefanopoulou, Huei Peng. IEEE Transactions on Control Systems Technology, 2006

302 citations recorded by the source corpus.

Subfields: Automotive Engineering, Electrical and Electronic Engineering, Electronic, Optical and Magnetic Materials

View Paper: https://www.semanticscholar.org/paper/63d4ebbb3923ef0f959c1dbc8c3bb34761be25b9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Scott Jason Moura
2. Duncan S. Callaway
3. Hosam K. Fathy
4. Branislav Hredzak
5. Jeffrey L. Stein
6. Vassilios G. Agelidis
7. Minsoo Jang

In Electrical and Electronic Engineering

1. Scott Jason Moura
2. Duncan S. Callaway
3. Hosam K. Fathy
4. Branislav Hredzak
5. Jeffrey L. Stein
6. Vassilios G. Agelidis
7. Minsoo Jang
8. Bin Wu

In Electronic, Optical and Magnetic Materials

1. Branislav Hredzak
2. Vassilios G. Agelidis
3. Minsoo Jang

Citations in the corpus

• A Model Predictive Control System for a Hybrid Battery-Ultracapacitor Power Source (2014, methodology): “As compared with [22], the configuration proposed in our paper uses two bidirectional dc/dc converters connecting a battery and an ultracapacitor to a dc bus.”
• Robust Model-Based Fault Diagnosis for PEM Fuel Cell Air-Feed System (2016, methodology): “The air compressor used to supply the oxygen to the cathode side is the core component and can consumes the power generated by the fuel cell up to 30% [31].”
• A Stochastic Optimal Control Approach for Power Management in Plug-In Hybrid Electric Vehicles (2011, methodology): “Such optimization can be performed offline for driv e cycles known a priori using deterministic dynamic programming (DDP) [7-10], and can also be performed online using opti mal model predictive control [11,12].”