Improving the energy efficiency of robots and increasing the time of operation has been a very hot research topic in recent times. There has been a lot of work on optimizing energy consumption, especially in mobile robots. Researchers have been focused on designing motion planning techniques along with velocity control to reduce the energy expenditure. But there has been a lack of a well-defined and a complete energy model that can act as a cost function for all the optimization algorithms. Having such a model not only provides a platform for energy loss control but can also give an idea about the nature of the losses and the cause of their occurrence. In this paper we first investigated the various energy loss components in a differential drive robot and presented a well-defined and a complete energy model. In order to validate our model we moved the robot with a specific velocity profile and measured all the losses.
This paper proposes dynamic modeling simulation for ac Surface Permanent Magnet Synchronous Motor (SPMSM) with the aid of MATLAB-Simulink environment. The proposed model would be used in many applications such as automotive, mechatronics, green energy applications, and machine drives. The modeling procedures are described and simulation results are presented. The validity of this dynamic model here is verified. Then, two genetic algorithm trials are presented to improve SPMSM performance. Maximum torque per ampere genetic algorithm function with maximum efficiency constrained is illustrated. Also, genetic algorithm maximum efficiency function constrained by GA maximum power factor is proposed. Simulations are implemented using MATLAB with its genetic algorithm toolbox. Finally, the required voltage to drive the motor at the desired improved characteristics is deduced for each case. All various characteristics are well depicted in the form of comparisons with such ones from original characteristics at rated voltage.
High Speed PM Generators driven by micro-turbines are widely used in Smart Grid System. So, this paper proposes comparative study among six classical, optimized and genetic analytical design cases for 400 kW output power at tip speed 200 m/s. These six design trials of High Speed Permanent Magnet Synchronous Generators (HSPMSGs) are: Classical Sizing; Unconstrained optimization for total losses and its minimization; Constrained optimized total mass with bounded constraints are introduced in the problem formulation. Then a genetic algorithm is formulated for obtaining maximum efficiency and minimizing machine size. In the second genetic problem formulation, we attempt to obtain minimum mass, the machine sizing that is constrained by the non-linear constraint function of machine losses. Finally, an optimum torque per ampere genetic sizing is predicted. All results are simulated with MATLAB, Optimization Toolbox and its Genetic Algorithm. Finally, six design examples comparisons are introduced with study of machines waveforms, THD and rotor losses.
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