Research on Lifetime Optimization of Unmanned Ship Lithium Battery Pack Power Supply System Based on Artificial Fish Swarm Algorithm

Pure electric vehicles develop rapidly all over the world. According to building the model of pure electric vehicle in the CRUISE software, first the power supply system parameters are designed and simulated, and then the power performance and feasibility of the model are verified. The design of CPS (composite power supply) which combined UC (ultra capacitor) with Li-B (lithium battery) can extend the life of the Li-B, and protect the Li-B in some way. Under the NEDC operating condition, the simulations of the SPS (single power supply) and the CPS are taken. The result shows that the variation of the Li-B SOC decrease by 8%, compared the CPS system with the SPS system, the comprehensive energy consumption economy is 6.25%.

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Parameter Matching Research of On-Board Synergic Electric Power Supply System Based on Secondary Development of ADVISOR

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.321-324.1351 ◽

2013 ◽

Vol 321-324 ◽

pp. 1351-1356

Author(s):

Jing Ming Zhang ◽

Hui Lin Wang

Keyword(s):

Simulation Model ◽

Electric Power ◽

Power Supply ◽

Power Supply System ◽

Supply System ◽

Battery Pack ◽

Secondary Development ◽

Electric Power Supply ◽

Vehicle Simulation ◽

Parameter Matching

Taking a series-parallel combined hybrid city bus as the prototype, the synergic electric power supply system (SEPS system) consisted of Ni-Mh battery pack and ultra-capacitor(UC)pack was designed to replace the original single electric power source which was battery pack. The element parameters were determined. By secondary development of ADVISOR, the simulation model and control strategy of the SEPS system and then the vehicle simulation model were built. Then the paper combined the ADVISOR with genetic algorithm to find the best capacity values of the battery pack and UC pack. The simulation results show that the vehicle with SEPS system can reduce the charge-discharge current of the battery pack, recapture more energy when braking which means better safety and fuel economy for the vehicle.

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Residential Uninterruptible Power Supply System with Renewable Energy Sources and Battery Pack

2018 IEEE 3rd International Conference on Intelligent Energy and Power Systems (IEPS) ◽

10.1109/ieps.2018.8559498 ◽

2018 ◽

Cited By ~ 5

Author(s):

V.V. Burlaka ◽

S.K. Podnebennaya ◽

S.V. Gulakov

Keyword(s):

Renewable Energy ◽

Power Supply ◽

Power Supply System ◽

Renewable Energy Sources ◽

Supply System ◽

Battery Pack ◽

Energy Sources ◽

Uninterruptible Power Supply ◽

Uninterruptible Power

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A lifetime optimization method of new energy storage module based on new artificial fish swarm algorithm

Advances in Mechanical Engineering ◽

10.1177/16878140211050843 ◽

2021 ◽

Vol 13 (9) ◽

pp. 168781402110508

Author(s):

Pengfei Zhi ◽

Yongshuang Qi ◽

Weiran Wang ◽

Haiyang Qiu ◽

Wanlu Zhu ◽

...

Keyword(s):

Energy Storage ◽

Optimization Method ◽

Step Length ◽

Artificial Fish Swarm Algorithm ◽

Fish School ◽

Battery Capacity ◽

New Energy ◽

Lifetime Optimization ◽

Artificial Fish Swarm ◽

Swarm Algorithm

The demand for new energy will continue to expand as the environment changes and fossil energy decreases. However, the instability of new energy has slowed down the development of new energy. The joint use of new energy and energy storage modules effectively solves the shortcomings of new energy. The article proposed a lifetime optimization method of new energy storage module based on new artificial fish swarm algorithm. Firstly the life model based on the battery capacity [Formula: see text], charging current [Formula: see text], and discharge current [Formula: see text] is built. Secondly, the deep learning method is used to improve the step length and speed change of artificial fish-school algorithm. Finally, the simulation platform detects the optimized parameters [Formula: see text]. The simulation results show that optimized parameters can help extend the life of the energy storage module.

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Orderly Discharging Strategy for Electric Vehicles at Workplace Based on Time-of-Use Price

Mathematical Problems in Engineering ◽

10.1155/2016/7025879 ◽

2016 ◽

Vol 2016 ◽

pp. 1-7 ◽

Cited By ~ 1

Author(s):

Lixing Chen ◽

Hong Zhang

Keyword(s):

Electric Vehicles ◽

Power Supply System ◽

Optimal Solution ◽

Supply System ◽

Penalty Function Methods ◽

Artificial Fish Swarm Algorithm ◽

Charging Station ◽

Scheduling Model ◽

Artificial Fish Swarm ◽

Simulation Results

According to the parking features of electric vehicles (EVs) and load of production unit, a power supply system including EVs charging station was established, and an orderly discharging strategy for EVs was proposed as well to reduce the basic tariff of producer and improve the total benefits of EV discharging. Based on the target of maximizing the annual income of producer, considering the total benefits of EV discharging, the electric vehicle aggregator (EVA) and time-of-use (TOU) price were introduced to establish the optimization scheduling model of EVs discharging. Furthermore, an improved artificial fish swarm algorithm (IAFSA) combined with the penalty function methods was applied to solve the model. It can be shown from the simulation results that the optimal solution obtained by IAFSA is regarded as the orderly discharging strategy for EVs, which could reduce the basic tariff of producer and improve the total benefits of EV discharging.

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Development of the algorithm for the selection of a wind generator-based autonomous power supply system

Power and Autonomous equipment ◽

10.32464/2618-8716-2019-2-1-8-16 ◽

2019 ◽

Vol 2 (1) ◽

pp. 8-16 ◽

Cited By ~ 1

Author(s):

P. A. Khlyupin ◽

G. N. Ispulaeva

Keyword(s):

Wind Turbines ◽

Power Supply ◽

Alternative Energy ◽

Power Supply System ◽

Supply System ◽

Power Generators ◽

Energy Devices ◽

Wind Generator ◽

Alternative Energy Sources ◽

Selection Of

Introduction: The co-authors provide an overview of the main types of wind turbines and power generators installed into wind energy devices, as well as advanced technological solutions. The co-authors have identified the principal strengths and weaknesses of existing wind power generators, if applied as alternative energy sources. The co-authors have proven the need to develop an algorithm for the selection of a wind generator-based autonomous power supply system in the course of designing windmill farms in Russia. Methods: The co-authors have analyzed several types of wind turbines and power generators. Results and discussions: The algorithm for the selection of a wind generator-based autonomous power supply system is presented as a first approximation. Conclusion: The emerging algorithm enables designers to develop an effective wind generator-based autonomous power supply system.

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