Grey Wolf Optimization Based Energy Management Strategy for Hybrid Electrical Vehicles

Brushless DC (BLDC) motors have a wide range of applications in these modern days, such as electric vehicles, industrial robots, washing machines, pumps, and blowers. The brushless DC motors have many advantages when compared to induction motors and conventional DC motors, such as better speed control, noiseless operation, high efficiency, less maintenance, and a long life. Along with these benefits, there is one major disadvantage known as cogging, which causes undesirable effects in the motor such as noises and vibrations. BLDC motors have been widely used in automation and industrial applications due to their attractive features. There are certain parameters to be considered while designing a BLDC motor, such as its dimensions, number of windings turns, type of magnetic materials used, required torque, output current, slot-to-depth ratio, efficiency, temperature rise, etc.

Section: Related Workmentioning

confidence: 99%

Impact of Stator Slot Shape on Cogging Torque of BLDC Motor

Kanagarathinam¹,

Manikandan

Ravivarman³

2023

“…However, they reveal several flaws in realistic PS implementations. Energy Storage System is studied in [12]. Due to their increased adaptability and robustness, fractional order (FO) controllers have been seeing more use in recent publication [11]- [14] [17].…”

Section: ░ 1 Introductionmentioning

confidence: 99%

A Novel Black Widow Optimized Controller Approach for Automatic Generation Control in Modern Hybrid Power Systems

Wadhwa,

Gupta

2023

This research paper demonstrates an application of the Black Widow Optimization (BWO) approach to address the issue of load-frequency control (LFC) in networked power systems. BWO is an innovative metaheuristic method that quickly suggests technique is initially evaluated on a non-reheat thermal-thermal (NRTT) power system spanning two areas of interconnection, and then it is applied to two different actual power systems: (a) a two-area thermal-thermal considering Generation Rate Constraint (GRC); and (b) a two-area having thermal, hydro, wind, solar, and gas systems. The BWO method uses two fitness functions based on integral time multiplied absolute error (ITAE) and integral square error (ISE) to optimize controller gains. The suggested BWO algorithm's performance has been compared to that of existing meta-heuristic optimization methods, such as grey wolf optimization (GWO), comprehensive learning particle swarm optimization (CLPSO), and an ensemble of parameters in differential evolution (EPSDE). The simulation results show that BWO's tuning skills are better than other population-based planning methods like CLPSO, EPSDE, and GWO. The ITAE value is enhanced by 33.28% (GWO), 40.28% (EPSDE), and 43.27% (CLPSO) when the BWO algorithm is used in conjunction with the PID Controller for thermal system.

“…(4) Two different types of energy storage technologies, including a battery and an ultra-capacitor, are used to provide reliable power to HEVs [12].…”

mentioning

confidence: 99%

Development and Application of an Energy Management System for Electric Vehicles Integrated with Multi-input DC-DC Bidirectional Buck-Boost Converter

Babu

Nayak

Mangu

2023

The rise in environmental pollution, demand for fossil fuels, and higher fuel economy vehicles has raised concerns about the creation of new and efficient transportation vehicles in recent days. These days, most developments in electric vehicles concentrate on making the vehicles more pleasant to ride in. Nonetheless, the emphasis now should be on energy and its most efficient use. To do this, you must give your attention to the origin of the automobile. The answer to this problem may be found in hybrid energy storage systems (HESS). This work is concerned with the design and implementation of an effective energy management system in electric vehicles (EVs) equipped with an active HESS consisting of a battery and a super capacitor via the incorporation of load sharing into this hybridization under a variety of load demand scenarios. To address the demands of high fuel efficiency vehicles, automotive firms are focusing on the development of diesel-engine operated vehicles, electric vehicles, fuel-cell vehicles, plug-in electric vehicles, and hybrid electric vehicles. A Multi-input Bidirectional Buck-Boost (MIB3) DC-DC converter is proposed in this dissertation to provide a greater conversion ratio to the input DC voltage. The multi-input converter recommended has fewer components and a simpler control method, making it more trustworthy and cost-effective. This converter also has bidirectional power flow functionality, making it suitable for charging the battery during regenerative braking in an electric or hybrid vehicle. Three different energy sources are used in the suggested topology: a photovoltaic (PV) panel, a battery, and an ultra-capacitor