Optimal Design of Switched Reluctance Motor Using Genetic Algorithm

Switched reluctance motor (SRM) is gaining more interest in both research and industry. Its simple structure without windings or permanent magnets on the rotor makes the motor robust and reliable with reduced manufacturing cost. The SRM also provides high starting torque and high efficiency over a wide range of speeds, which is strongly desired for electric vehicles’ applications. However, these advantages of switched reluctance motors come with some challenges. Torque ripples, low power density, and temperature rise are common questions about SRM. This paper utilizes multi-objective optimization of SRM design to get most of the SRM desired characteristics with minimization of the machine’s common drawbacks. The optimization process has considered twelve variables and five objective functions. These functions include average torque, efficiency, iron weight, torque-ripples, and maximum temperature rise. The electromagnetic analysis of each candidate is performed by the finite elements method (FEA). The performance indices of SRM are calculated based on FEA analysis results via calculations that compensate for accuracy and computation time. The multi-objective genetic algorithm technique (MOGA) combines the objective functions into a single objective function. Verifying the optimal design comprises generating the efficiency map, torque profile, and dynamic simulation of the motor. This paper mainly focuses on the design and optimization of SRM to fulfill the general requirements of electric vehicle applications

Optimal Design of Switched Reluctance Motor Using Genetic Algorithm

Switched reluctance motor (SRM) is gaining more interest in both research and industry. Its simple structure without windings or permanent magnets on the rotor makes the motor robust and reliable with reduced manufacturing cost. The SRM also provides high starting torque and high efficiency over a wide range of speeds, which is strongly desired for electric vehicles’ applications. However, these advantages of switched reluctance motors come with some challenges. Torque ripples, low power density, and temperature rise are common questions about SRM. This paper utilizes multi-objective optimization of SRM design to get most of the SRM desired characteristics with minimization of the machine’s common drawbacks. The optimization process has considered twelve variables and five objective functions. These functions include average torque, efficiency, iron weight, torque-ripples, and maximum temperature rise. The electromagnetic analysis of each candidate is performed by the finite elements method (FEA). The performance indices of SRM are calculated based on FEA analysis results via calculations that compensate for accuracy and computation time. The multi-objective genetic algorithm technique (MOGA) combines the objective functions into a single objective function. Verifying the optimal design comprises generating the efficiency map, torque profile, and dynamic simulation of the motor. This paper mainly focuses on the design and optimization of SRM to fulfill the general requirements of electric vehicle applications

Fish farm management and microcontroller based aeration control system

Fisheries are required to grant convenient environmental conditions for fish growth with minimum cost afford.  Providing these environmental conditions should essentially correlate fish type, pond dimensions, water properties, and weather conditions to the fish growth rate, feeding and metabolism.  The large uncertainty margin of such parameters relations and effects drives the farmers to have economically inefficient practices in their farms.  The present work was divided into two parts.  The first part introduced an interactive Microsoft Excel spreadsheets as a decision support system (DSS) for the purposes of fish farm area planning according to the different required purposes of ponds, water evaluation to insure the most suitable environment of fish growth, and mechanical aeration management.  The design of this DSS took the simplicity of required input data and data output into consideration.  The second part was a microcontroller based open loop control system for mechanical aeration process based on the calculations of the DSS.  The aeration management part input and output data fed to the control system with a specially developed program using µC-language.  This program performs the calculations of aeration requirements and energy demands based on the DSS calculations.  Furthermore, the controller had the feature of working from isolated power supply or in collaboration with renewable energy system.  These utilities have been created to be suitable for three fish types, which are Mullet, Tilapia, and Carp fish.  These types have a wide acceptance in the aquaculture activities under warm water conditions.  The data obtained from the calculations of the spreadsheet under simulated and real field conditions were compared to a reference data. The spreadsheet showed an agreement with the reference values.  The control systems succeed to operate 1hp-3phase induction motor for a time that was identical to the required aeration time calculated through the DSS.  It was recommended to rely on the created DSS and the control system for farm area planning, water environment evaluation, and mechanical aeration management and operation.  In addition, improvements for the control system should be carried out to be a real-time system especially with water quality parameters considering system power requirements and operating costs.   Keywords: control system, fish farm, management, microcontroller, aeration

BACH ARRAY LINEAR GENERATOR FOR WAVE ENERGY CONVERTERS

linear generators have been proposed as a proper power takeoff system for direct-drive wave energy conversion. Coupled directly to a reciprocating wave energy device, it was declared that linear generators could be a valuable replacement for hydraulic and pneumatic systems. In this paper, the design and performance evaluation of permanent magnet linear generator that implements Halbach array arrangement is established. The designed generator is suitable for direct energy extraction from sea waves at small wave amplitude. The electromagnetic design is performed using finite element method and space harmonic analysis. A comparative study is performed between Halbach array and conventional air-cored linear generators to show the effectiveness of the proposed design. The equivalent circuit based model is utilized to investigate the dynamic performance of the Halbach array generator. The simulated dynamic performance of the designed generator clarifies that the implementation of Halbach array arrangement would improve energy extraction and voltage waveform

Multi-objective optimization of switched reluctance machine design using Jaya algorithm (MO-Jaya)

The switched reluctance machine (SRM) design is different from the design of most of other machines. SRM has many design parameters that have non-linear relationships with the performance indices (i.e., average torque, efficiency, and so forth). Hence, it is difficult to design SRM using straight forward equations with iterative methods, which is common for other machines. Optimization techniques are used to overcome this challenge by searching for the best variables values within the search area. In this paper, the optimization of SRM design is achieved using multi-objective Jaya algorithm (MO-Jaya). In the Jaya algorithm, solutions are moved closer to the best solution and away from the worst solution. Hence, a good intensification of the search process is achieved. Moreover, the randomly changed parameters achieve good search diversity. In this paper, it is suggested to also randomly change best and worst solutions. Hence, better diversity is achieved, as indicated from results. The optimization with the MO-Jaya algorithm was made for 8/6 and 6/4 SRM. Objectives used are the average torque, efficiency, and iron weight. The results of MO-Jaya are compared with the results of the non-dominated sorting genetic algorithm (NSGA-II) for the same conditions and constraints. The optimization program is made in Lua programming language and executed by FEMM4.2 software. The results show the success of the approach to achieve better objective values, a broad search, and to introduce a variety of optimal solutions

Finite element based overall optimization of switched reluctance motor using multi-objective genetic algorithm (NSGA-II)

The design of switched reluctance motor (SRM) is considered a complex problem to be solved using conventional design techniques. This is due to the large number of design parameters that should be considered during the design process. Therefore, optimization techniques are necessary to obtain an optimal design of SRM. This paper presents an optimal design methodology for SRM using the non-dominated sorting genetic algorithm (NSGA-II) optimization technique. Several dimensions of SRM are considered in the proposed design procedure including stator diameter, bore diameter, axial length, pole arcs and pole lengths, back iron length, shaft diameter as well as the air gap length. The multi-objective design scheme includes three objective functions to be achieved, that is, maximum average torque, maximum efficiency and minimum iron weight of the machine. Meanwhile, finite element analysis (FEA) is used during the optimization process to calculate the values of the objective functions. In this paper, two designs for SRMs with 8/6 and 6/4 configurations are presented. Simulation results show that the obtained SRM design parameters allow better average torque and efficiency with lower iron weight. Eventually, the integration of NSGA-II and FEA provides an effective approach to obtain the optimal design of SRM

Technical and Economical Investigation of Renewable Energy Sources for Supplying Offshore Oil production Facilities at Gulf of Suez Area

The Gulf of Suez is highly susceptible to economic and energy security due to the heavy need for imported fossil fuels. The energy produced from fossil fuels causes serious environmental pollution. So, it is important to find other clean sources of energy for stabilizing the released amount of carbon dioxide. Gulf of Suez has the potential to develop clean Solar Photovoltaic (PV) and wind systems to improve economic and environmental performance. This paper proposes a combination of floating solar panels (FSP) and offshore wind turbines to solve the main critical issues, such as the land area required for a large number of cells and the space required for wind turbines. In addition to their good economical and environmental benefits. A simplified model is provided to investigate the replacement of traditional generating units (Diesel and Gas operated) supplying offshore oil production field facilities at the Gulf of Suez area with a mix of renewable resources. The load flow analysis is carried out for the model and the cost is calculated and compared for four schemas, the traditional generating, Wind-Gas, PV-Gas, and PV-Wind-Gas hybrid system. From the techno-economic analysis and comparing environmental benefits, floating solar systems and offshore wind turbines can provide a good solution to the existing problems of energy needs with environmental impacts considered

Optimal Sizing of Standalone PV-Wind Hybrid Energy System in Rural Area North Egypt

This paper studies the sizing of stand-alone renewable energy system applied in rural areas in the north of Egypt. The available renewable energy sources in these areas are investigated to be integrated to supply the different types of electrical loads. The quality and quantity of these sources over various weather and climate changes are studied to construct a robust energy system. The load demand in such areas is determined according to all activities require electrical energy. This study considers the different economic levels and technologies which affect the load demand value. The technique and economical indices required to obtain the optimal are investigated and applied in the various estimated cases. The genetic algorithm (GA) technique is applied to determine the size and number of photovoltaic panels and wind turbines. The obtained solution takes into account the loss of power supply probability and the minimization of system cost. This study presents an essential phase in the sustainable development of such rural areas

Correlation of Muscle Invasion in Bladder Cancer with Cell Adhesion Properties and Oncoprotein Overexpression Using E-Cadherin and HER2/neu Immunohistochemical Markers.

BACKGROUND: Most of bladder cancers are proven to be of urothelial origin (transitional cell carcinomas). Above 75% of them are of non-muscle invasive bladder cancer (NMIBC) type at presentation and the remainder are MIBC. Recent studies suggest that both are most probably two different categories based on both the histopathological and molecular features. The comprehensive understanding of the biomarkers expression in both categories will help in understanding the molecular event underlying each of them and may provide possible chances for targeted therapeutic options. AIM: This study aims to study the differential expression of both E-cadherin and human epidermal growth factor receptor-2 (HER2) in the two categories of bladder cancer NMIBCs and MIBCs. MATERIALS AND METHODS: A total of 40 blocks were collected retrospectively from cases of cancer bladder, segregated as 20 cases NMIBCs and 20 cases MIBCs, subjected for E-cadherin and HER2 immunostaining. RESULTS: E-cadherin showed positive expression in 65% of cases of NMI group and in 10% of the MI group, with high statistical significance (p < 0.001). Regarding HER2, positive expression was seen in 25% of NMI cases and in 90% of MI cases, with statistical significance (p < 0.001). Comparison of the results of both markers and their correlation per case showed that 90% of tumors with muscle invasion were E-cadherin negative and HER2 positive. CONCLUSION: The significant association of loss of E-cadherin immunohistochemistry expression and positive HER2 overexpression in MIBC versus NMIBC figured out more differences between the two categories and added to the understanding of their biology. The possibility of validation of HER2-targeted therapy in MIBC cases is now strongly suggested