scholarly journals Experimental Comparison of Three Real-Time Optimization Strategies Applied to Renewable/ FC-Based Hybrid Power Systems Based on Load-Following Control

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3537 ◽  
Author(s):  
Nicu Bizon ◽  
Mihai Oproescu
Keyword(s):  
Power Systems ◽  
Real Time ◽  
Fuel Consumption ◽  
Fuel Economy ◽  
Experimental Comparison ◽  
Hybrid Power Systems ◽  
Hybrid Power ◽  
Load Following ◽  
Time Optimization ◽  
Real Time Optimization

Besides three different real-time optimization strategies analyzed for the Renewable/ Fuel Cell Hybrid Power Systems (REW/FC-HPS) based on load-following (LFW) control, a short but critical assessment of the Real-Time Optimization (RTO) strategies is presented in this paper. The advantage of power flow balance on the DC bus through the FC net power generated using the LFW control instead of using the batteries’ stack is highlighted in this study. As LFW control consequence, the battery operates in charge-sustained mode and many advantages can be exploited in practice such as: reducing the size of the battery and maintenance cost, canceling the monitoring condition of the battery state-of-charge etc. The optimization of three FC-HPSs topologies based on appropriate RTO strategy is performed here using indicators such as fuel economy, fuel consumption efficiency, and FC electrical efficiency. The challenging task to optimize operation of the FC-HPS under unknown profile of the load demand is approached using an optimization function based on linear mix of the FC net power and the fuel consumption through the weighting coefficients knet and kfuel. If optimum values are chosen, then a RTO switching strategy can improve even further the fuel economy over the entire range of load.

Air Flow Real-time Optimization Strategy for Fuel Cell Hybrid Power Sources with Fuel Flow Based on Load-following

Fuel Cells ◽  
2018 ◽  
Vol 18 (6) ◽  
pp. 809-823 ◽  
Author(s):  
N. Bizon ◽  
G. Iana ◽  
E. Kurt ◽  
P. Thounthong ◽  
M. Oproescu ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Real Time ◽  
Cell Hybrid ◽  
Optimization Strategy ◽  
Power Sources ◽  
Hybrid Power ◽  
Load Following ◽  
Fuel Flow ◽  
Time Optimization ◽  
Real Time Optimization

scholarly journals Improving the Fuel Economy and Battery Lifespan in Fuel Cell/Renewable Hybrid Power Systems Using the Power-Following Control of the Fueling Regulators

2020 ◽  
Vol 10 (22) ◽  
pp. 8310
Author(s):  
Nicu Bizon ◽  
Mihai Oproescu ◽  
Phatiphat Thounthong ◽  
Mihai Varlam ◽  
Elena Carcadea ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Power Systems ◽  
Fuel Economy ◽  
Storage System ◽  
Energy Storage System ◽  
Power Converter ◽  
Hybrid Power Systems ◽  
Safe Operation ◽  
Hybrid Power ◽  
Load Demand

In this study, the performance and safe operation of the fuel cell (FC) system and battery-based energy storage system (ESS) included in an FC/ESS/renewable hybrid power system (HPS) is fully analyzed under dynamic load and variable power from renewable sources. Power-following control (PFC) is used for either the air regulator or the fuel regulator of the FC system, or it is switched to the inputs of the air and hydrogen regulators based on a threshold of load demand; these strategies are referred to as air-PFC, fuel-PFC, and air/fuel-PFC, respectively. The performance and safe operation of the FC system and battery-based ESS under these strategies is compared to the static feed-forward (sFF) control used by most commercial strategies implemented in FC systems, FC/renewable HPSs, and FC vehicles. This study highlights the benefits of using a PFC-based strategy to establish FC-system fueling flows, in addition to an optimal control of the boost power converter to maximize fuel economy. For example, the fuel economy for a 6 kW FC system using the air/fuel-PFC strategy compared to the strategies air-PFC, fuel-PFC, and the sFF benchmark is 6.60%, 7.53%, and 12.60% of the total hydrogen consumed by these strategies under a load profile of up and down the stairs using 1 kW/2 s per step. For an FC/ESS/renewable system, the fuel economy of an air/fuel-PFC strategy compared to same strategies is 7.28%, 8.23%, and 13.43%, which is better by about 0.7% because an FC system operates at lower power due to the renewable energy available in this case study.

Real-Time Implementation of Optimal Energy Management in Hybrid Electric Vehicles: Globally Optimal Control of Acceleration Events

2020 ◽  
Vol 142 (8) ◽  
Author(s):  
Zachary D. Asher ◽  
David A. Trinko ◽  
Joshua D. Payne ◽  
Benjamin M. Geller ◽  
Thomas H. Bradley
Keyword(s):  
Optimal Control ◽  
Real Time ◽  
Fuel Economy ◽  
Control Strategy ◽  
Limited Information ◽  
Optimal Control Strategy ◽  
Time Optimization ◽  
Vehicle Operation ◽  
Operation Knowledge ◽  
Real Time Optimization

Abstract Widely published research shows that significant fuel economy improvements through optimal control of a vehicle powertrain are possible if the future vehicle velocity is known and real-time optimization calculations can be performed. In this research, however, we seek to advance the field of optimal powertrain control by limiting future vehicle operation knowledge and using no real-time optimization calculations. We have realized optimal control of acceleration events (AEs) in real-time by studying optimal control trends across 384 real world drive cycles and deriving an optimal control strategy for specific acceleration event categories using dynamic programming (DP). This optimal control strategy is then applied to all other acceleration events in its category, as well as separate standard and custom drive cycles using a look-up table. Fuel economy improvements of 2% average for acceleration events and 3.9% for an independent drive cycle were observed when compared to our rigorously validated 2010 Toyota Prius model. Our conclusion is that optimal control can be implemented in real-time using standard vehicle controllers assuming extremely limited information about future vehicle operation is known such as an approximate starting and ending velocity for an acceleration event.

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