Hybrid vehicles, which refer to vehicles with two power sources, are important for improving the fuel economy, power and reducing pollutant emissions of vehicles. In order to solve the shortcomings of the existing electric hybrid system research, this paper briefly discusses the development environment and hybrid vehicle parameters of the electric hybrid system based on the artificial fish swarm algorithm, based on the discussion of the type of electric hybrid system and the artificial fish swarm algorithm. And the design of the electric hybrid power system energy control model and the system architecture of the artificial fish swarm algorithm are discussed, and finally the electric hybrid power system built by incorporating the artificial fish swarm algorithm and the improved artificial fish swarm algorithm are experimentally analyzed. The experimental data show that the simulated annealing global artificial fish swarm algorithm consumes less than 3598 energy on average for the electric hybrid power system, which is lower than the artificial fish swarm algorithm and the global artificial fish swarm algorithm. Therefore, it is verified that the simulated annealing global artificial fish swarm algorithm has good control effect on the energy of the electric hybrid power system.

Norizan Ahmad. Artificial Fish Swarm Algorithm Based Electric Hybrid Power System. Kinetic Mechanical Engineering (2020), Vol. 1, Issue 3: 42-49. https://doi.org/10.38007/KME.2020.010306.

[1] Mab A , Nha B , Gme A . An efficient design of LC-compensated hybrid wireless power transfer system for electric vehicle charging applications. Alexandria Engineering Journal, 2020, 61( 8):6565-6580. https://doi.org/10.1016/j.aej.2020.12.016

[2] Meyer, Daniel, Senner, et al. Evaluating a heart rate regulation system for human-electric hybrid vehicles. Proceedings of the Institution of Mechanical Engineers, Part P. Journal of Sports Engineering and Technology, 2018, 232(2):102-111. https://doi.org/10.1177/1754337117710069

[3] Tworek B . Development of electric systems for hybrid and electric vehicles. Przeglad Elektrotechniczny, 2018, 94(6):152-154. https://doi.org/10.15199/48.2018.06.30

[4] Pruski P , Paszek S . Analysis of transient waveforms in a power system at asymmetrical short-circuits. Przeglad Elektrotechniczny, 2020, 96(2):26-29. https://doi.org/10.15199/48.2020.02.05

[5] Anderson J . NYISO takes preliminary steps to improving its power system planning process. Platts Megawatt Daily, 2018, 23(222):6-8.

[6] Rifat, Hazari, Mohammad, et al. Fuzzy Logic based Virtual Inertia Control of DFIG based Wind Generator for Stability Improvement of Hybrid Power System.2018, 138(8):733-744. https://doi.org/10.1541/ieejpes.138.733

[7] Buragohain M , Das N K D . A neoteric closed loop feedback controller based on correlative-elemental curvature algorithm. Circuit World, 2020, 48(3):341-353. https://doi.org/10.1108/CW-06-2020-0107

[8] Ek A , As B . Evaluation model for multi-energy carrier facilities within the control energy market. Procedia CIRP, 2020, 99:537-542. https://doi.org/10.1016/j.procir.2020.03.073

[9] Abdelkhalik O , Zou S . Control of Wave Energy Converters Using A Simple Dynamic Model. Sustainable Energy, IEEE Transactions on, 2019, 10(2):579-585. https://doi.org/10.1109/TSTE.2018.2838768

[10] Yamamoto M , Kawabe K , Nanahara T . Optimization of Load Frequency Control with Battery Energy Storage Systems -- Application of Spectral Analysis Techniques --. IFAC-PapersOnLine, 2019, 52( 4):252-257. https://doi.org/10.1016/j.ifacol.2019.08.202

[11] Rodriguez-Cortes H . A swinging up controller for the furuta pendulum based on the total energy control system approach. Kybernetika, 2019, 55(2):402-421. https://doi.org/10.14736/kyb-2019-2-0402

[12] dos, Santos, Paloma, et al. Chemical and conformational control of the energy gaps involved in the thermally activated delayed fluorescence mechanism. Journal of Materials Chemistry, C. materials for optical and electronic devices, 2018, 6(18):4842-4853. https://doi.org/10.1039/C8TC00991K

[13] Shanthi G , Sundarambl M . Design and Implementation of Monitoring and Control Algorithm for Energy Conservation in Building. International journal of computing & information technology, 2018, 10(1):83-92.

[14] Khazaei J , Nguyen D H . Multi-Agent Consensus Design for Heterogeneous Energy Storage Devices With Droop Control in Smart Grids. IEEE Transactions on Smart Grid, 2019, 10(2):1395-1404. https://doi.org/10.1109/TSG.2017.2765241

[15] Sjostrom S , Klintenas E , Johansson P , et al. Optimized model-based control of main mine ventilation air flows with minimized energy consumption. 2020, 030(004):P.533-539. https://doi.org/10.1016/j.ijmst.2020.05.016

[16] Mudaliyar S , Mishra S . Coordinated Voltage Control of a Grid Connected Ring DC Microgrid With Energy Hub. Smart Grid, IEEE Transactions on, 2019, 10(2):1939-1948. https://doi.org/10.1109/TSG.2017.2783972

[17] Saleem E , Dao T M , Liu Z . Multiple-Objective Optimization and Design of Series-Parallel Systems Using Novel Hybrid Genetic Algorithm Meta-Heuristic Approach. 2018, 6(3):532-555. https://doi.org/10.4236/wjet.2018.63032

[18] Singh, Karamdeep, Kaur, et al. Enhanced gain in S plus C band utilizing TDFA-FRA hybrid amplifier in cascaded and parallel configurations at reduced channel spacings for DWDM systems. Journal of optoelectronics and advanced materials, 2018, 20(1-2):27-32.