A Modified MPC-Based Optimal Strategy of Power Management for Fuel Cell Hybrid Vehicles

Chen, Hao; Chen, Jian; Lu, Haichang; Yan, Chizhou; Liu, Zhiyang

doi:10.1109/tmech.2020.2993811

Cited by 42 publications

(12 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A recent paper stands out, showing an interesting approach to using linear time by varying MPC with the goal of controlling the power of the fuel cell in simulated driving conditions while imposing constraints on many critical physical quantities (e.g., pressure, temperature, humidity) ensuring safe operation of the fuel cell, partly sharing the paradigm of this paper [19]. MPC shows the most promise compared to other control strategies in the sense that it exhibits all the elements necessary for safe and efficient operation of multivariable constrained systems [20]. However, even though the advantages of MPC over PI are known and obvious, it is usually not used in industries for a few reasons.…”

Section: Introductionmentioning

confidence: 99%

Model-Predictive-Control-Based Reference Governor for Fuel Cells in Automotive Application Compared with Performance from a Real Vehicle

2021

View full text Add to dashboard Cite

In this paper, a real-time capable reference governor superordinate model predictive controller (RG-MPC) is developed for fuel cell (FC) control suitable for automotive application. The RG-MPC provides reference trajectories for the subordinate proportional-integral (PI) controllers, which act directly on the FC system. Antiwindup and decoupling schemes, which are common problems in multivariable PI control, are unnecessary, given that the RG-MPC can inherently consider constraints and multivariable systems. The PI dynamics are incorporated into the prediction model used for control, ensuring the feasibility of the provided references for the PI controllers. The successive linearization technique is used in the RG-MPC to cope with the model’s nonlinear nature in real-time. The concept has been illustrated in a simulation scenario featuring efficient and safe power control of an FC stack in automotive application using real driving data obtained from an in-house-built FC vehicle. This work is the first step towards upgrading an existing, PI-based control scheme without the necessity of completely rebuilding the interface.

show abstract

Section: Introductionmentioning

confidence: 99%

Model-Predictive-Control-Based Reference Governor for Fuel Cells in Automotive Application Compared with Performance from a Real Vehicle

2021

View full text Add to dashboard Cite

show abstract

“…Compared to a conventional model-based control method, the authors discovered that the MPC-based control strategy enhanced the performance of the VSI. An MFPC-based control technique for a VSI in an electric vehicle application was suggested in other research [26]. The authors forecasted the battery level of charge and the load demand using a prediction model based on previous data.…”

Section: Introductionmentioning

confidence: 99%

Model-Free Predictive Current Control of a 3-φ Grid-Connected Neutral-Point-Clamped Transformerless Inverter

et al. 2023

View full text Add to dashboard Cite

Utility grid-tied photovoltaic (PV) installations are becoming a typical component of the current electrical energy grid. The adoption of transformerless inverters has recently changed the topology of these systems. Despite being small, inexpensive, and effective, transformerless inverters have a recurring leakage current issue. Numerous studies are being conducted to improve its performance and bring the leakage current down to acceptable levels. The studies propose three tracks for addressing the leakage current problem of transformerless PV systems: the control technique, the inverter modulation, and the inverter topology. This study applies the model-free predictive control (MFPC) technique to a grid-connected NPC 3-φ transformerless converter powered by a PV panel. An LCL filter connects the transformerless inverter to the grid. The system model considers the grid filter components and the internal impedance of the utility grid. The proposed system’s discrete model is established before describing the MFPC controller’s algorithm. The suggested system is simulated in MATLAB using the MFPC and a standard PI current controller with SVPWM modulation. According to the simulation’s findings, the MFPC controller performs best regarding current spectrum, THD, and earth leakage current. Additionally, MFPC-based systems are more efficient than those that use PI controllers.

show abstract

“…Optimization-based strategies can be divided into real-time optimization strategies and global optimization strategies [20,21]. Real-time optimization strategies such as model predictive control (MPC) [22] and the equivalent consumption minimum strategy (ECMS) [23] have the advantage of high real-time performance, but only local optimum can be achieved. Tao J. et al, proposed an algorithmic framework combining a Q-learning and genetic algorithm for the power split between the fuel cell and supercapacitor of a vehicle, and simulation results show that the SOC of the supercapacitor can be sustained within the desired safe range, while reducing hydrogen consumption [24].…”

Section: Introductionmentioning

confidence: 99%

Research on Energy Management Strategy of Fuel Cell Vehicle Based on Multi-Dimensional Dynamic Programming

et al. 2022

View full text Add to dashboard Cite

The powertrain of a fuel cell vehicle typically consists of two energy sources: a proton electrolyte membrane fuel cell (PEMFC) stack and a battery package. In this paper, multi-dimensional dynamic programming (MDDP) is used to solve the energy management strategy (EMS) of fuel cell hybrid powertrain. This study built a fuel cell hybrid powertrain model, in which the battery model is built based on the Thevenin equivalent circuit. In order to improve the calculating efficiency and maintain the accuracy of the algorithm, the state variables in each stage are divided into primary and secondary. In the reverse solution process, the corresponding relationship between the multi state variables grid and the optimal cumulative function has been changed from three-dimensional to two-dimensional. The EMS based on MDDP is applied to component sizing of a commercial vehicle. Simulations were conducted using MATLAB under the C-WTVC working condition. By analyzing the fuel economy and system durability, the optimal component combination of comprehensive performance is obtained. Compared with the EMS based on dynamic programming (DP), the proposed method effectively improves the calculation accuracy: the hydrogen consumption can be reduced by 3.10%, and the durability of the fuel cell and battery can be improved by 1.08% and 0.13%, respectively.

show abstract

A Modified MPC-Based Optimal Strategy of Power Management for Fuel Cell Hybrid Vehicles

Cited by 42 publications

References 32 publications

Model-Predictive-Control-Based Reference Governor for Fuel Cells in Automotive Application Compared with Performance from a Real Vehicle

Model-Predictive-Control-Based Reference Governor for Fuel Cells in Automotive Application Compared with Performance from a Real Vehicle

Model-Free Predictive Current Control of a 3-φ Grid-Connected Neutral-Point-Clamped Transformerless Inverter

Research on Energy Management Strategy of Fuel Cell Vehicle Based on Multi-Dimensional Dynamic Programming

Contact Info

Product

Resources

About