Research article

Dynamic modeling and simulation of the MUN Explorer autonomous underwater vehicle with a fuel cell system

  • Received: 23 October 2019 Accepted: 03 January 2020 Published: 03 February 2020
  • The actual power system of the MUN Explorer Autonomous Underwater Vehicles (AUVs) uses 11 Lithium-ion (Li-ion) batteries as a main energy source. The batteries are directly connected into the BLDC motor to run the MUN Explorer for the desired operating sequence. This paper presents a dynamic model of the MUN Explorer AUV including a fuel cell system to run under the same operating conditions as suggested by its manual. A PI controller was applied into the dynamic model to maintain the operating conditions such as motor speed, DC bus voltage and the load torque, due to its advantages and simplicity for tuning technique. The MUN Explorer AUV dynamic model with a fuel cell is a proposed system to increase the power capacity, it is better to use a simple controller to see the system behaviors. The simulation of the entire system dynamics model along with the proportional-integral (PI) controller is done in MATLAB / Simulink. The simulation results are included in the paper. The DC bus voltage is measured at 48 V, and the motor speed is 20 (rad/s), which is equivalent to 190 (rpm). The power profile of the fuel cell and battery are presented and plotted against time. The PI controller gives satisfactory results in terms of maintaining the same operating conditions of the MUN Explorer AUV with a fuel cell.

    Citation: Mohamed M. Albarghot, Mohamed T. Iqbal, Kevin Pope, Luc Rolland. Dynamic modeling and simulation of the MUN Explorer autonomous underwater vehicle with a fuel cell system[J]. AIMS Electronics and Electrical Engineering, 2020, 4(1): 114-131. doi: 10.3934/ElectrEng.2020.1.114

    Related Papers:

  • The actual power system of the MUN Explorer Autonomous Underwater Vehicles (AUVs) uses 11 Lithium-ion (Li-ion) batteries as a main energy source. The batteries are directly connected into the BLDC motor to run the MUN Explorer for the desired operating sequence. This paper presents a dynamic model of the MUN Explorer AUV including a fuel cell system to run under the same operating conditions as suggested by its manual. A PI controller was applied into the dynamic model to maintain the operating conditions such as motor speed, DC bus voltage and the load torque, due to its advantages and simplicity for tuning technique. The MUN Explorer AUV dynamic model with a fuel cell is a proposed system to increase the power capacity, it is better to use a simple controller to see the system behaviors. The simulation of the entire system dynamics model along with the proportional-integral (PI) controller is done in MATLAB / Simulink. The simulation results are included in the paper. The DC bus voltage is measured at 48 V, and the motor speed is 20 (rad/s), which is equivalent to 190 (rpm). The power profile of the fuel cell and battery are presented and plotted against time. The PI controller gives satisfactory results in terms of maintaining the same operating conditions of the MUN Explorer AUV with a fuel cell.


    加载中


    [1] Cirrincione M, Cossentino M, Gaglio S, et al. (2009) Intelligent energy management system. IEEE Int Conf Ind Informatics 232-237.
    [2] Barchi G, Miori G, Moser D, et al. (2018) A Small-Scale Prototype for the Optimization of PV Generation and Battery Storage through the Use of a Building Energy Management System. 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe).
    [3] Kumaraswamy VK and Quaicoe JE (2016) Tracking techniques for the PEMFC in portable applications. 2016 IEEE Electrical Power and Energy Conference (EPEC).
    [4] Motapon SN, Dessaint LA, Al-Haddad K (2014) A comparative study of energy management schemes for a fuel-cell hybrid emergency power system of more-electric aircraft. IEEE T Ind Electron 61: 1320-1334. doi: 10.1109/TIE.2013.2257152
    [5] Albarghot MM, Iqbal MT, Pope K, et al. (2019) Sizing and Dynamic Modeling of a Power System for the MUN Explorer Autonomous Underwater Vehicle Using a Fuel Cell and Batteries. J Energy 2019: 4531497.
    [6] Motapon SN, Lupien-Bedard A, Dessaint LA, et al. (2017) A Generic Electrothermal Li-ion Battery Model for Rapid Evaluation of Cell Temperature Temporal Evolution. IEEE T Ind Electron 64: 998-1008.
    [7] Xie W, Wang JS, Wang HB (2019) PI Controller of Speed Regulation of Brushless DC Motor Based on Particle Swarm Optimization Algorithm with Improved Inertia Weights. Math Probl Eng 2019: 1-12.
    [8] Wang Y, Sun Z, Chen Z (2019) Development of energy management system based on a rule-based power distribution strategy for hybrid power sources. Energy 175: 1055-1066. doi: 10.1016/j.energy.2019.03.155
    [9] Wang Y, Sun Z, Chen Z (2019) Energy management strategy for battery/supercapacitor/fuel cell hybrid source vehicles based on finite state machine. Appl Energy 254: 113707. doi: 10.1016/j.apenergy.2019.113707
    [10] Wang Y, Sun Z, Li X, et al. (2019) A comparative study of power allocation strategies used in fuel cell and ultracapacitor hybrid systems. Energy 189: 116142. doi: 10.1016/j.energy.2019.116142
    [11] Wang Y, Li X, Wang L, et al. (2019) Multiple-grained velocity prediction and energy management strategy for hybrid propulsion systems. J Energy Storage 26: 100950. doi: 10.1016/j.est.2019.100950
    [12] Görgün H (2006) Dynamic modelling of a proton exchange membrane (PEM) electrolyzer. Int J Hydrogen Energy 31: 29-38. doi: 10.1016/j.ijhydene.2005.04.001
    [13] Rigatos G and Siano P (2016) A PEM fuel cells control approach based on differential flatness theory. 2016 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM) 2: 1004-1009.
    [14] Souleman NM, Tremblay O, Dessaint LA (2009) A generic fuel cell model for the simulation of fuel cell vehicles. 2009 IEEE Vehicles Power and Propulsion Conference 1722-1729.
    [15] Geraee S, Shafiei M, Sahami AR, et al. (2017) Position sensorless and adaptive speed design for controlling brushless DC motor drives. 2017 North American Power Symposium NAPS.
  • Reader Comments
  • © 2020 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(5202) PDF downloads(642) Cited by(3)

Article outline

Figures and Tables

Figures(17)  /  Tables(2)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog