Sensorless speed and position control of permanent magnet BLDC motor using particle swarm optimization and ANFIS

This paper describes the operation of a Permanent Magnet Brushless Direct Current (PMBLDC) motor without a position sensor. In this case, the sensorless operation is enhanced by an effective hybrid technique that detects the back electromotive force (Back EMF) of the zero crossing point (ZCP) from the terminal voltages. The Adaptive Neuro Fuzzy Interference System (ANFIS) controller, which is based on Particle Swarm Optimization (PSO) and uses PSO to train its operation, is combined in the proposed hybrid analysis. The PMBLDC motor's ANFIS controller receives the line voltages as input, and it uses this information to estimate the sample signals that are then sent to the ZCP detection circuit. Appropriate commutation control of the inverter is generated by the ZCP detecting circuit. By varying the ANFIS consequent parameters, the PSO algorithm iterates until the error between the sample output and the real training data reaches a low value. The MATLAB/Simulink platform is utilized to implement the suggested sensorless controller action. To verify the controller's performance, a comparison with the other soft computing methods is also carried out

Simulink and real-time implementation of the E-cycle for measuring the reliability of the model using sensors

Utilization of rechargeable battery based bicycles has been significantly increased in India. In this study, battery powered electric vehicles have been implemented in MATLAB 2013a Simulink and real-time hardware systems. In order to design and integrate a working model of electric cycle, one needs to know about the different components involved in a system, such as lithium-ion batteries, Brushless DC motor (BLDC), and controller systems. The detailed study about the component selection has been described in this study. The drive testing has been implemented in both Simulink and real time respectively. Within a single charging system, the proposed model of electric cycle has been derived up to 25 kilo-meter up to speed of 30 kilo-meter per second respectively. The characteristics of electric vehicles such as torque (N-m) versus time (s), speed (km/h) versus time (s) and distance (km) versus time (s) have been discussed in this study. Based on characteristics study, reliability of the electric vehicle model has been enhanced in electric bicycle system by physical model confirmation

Modelling and performance analysis of improved incremental conductance MPPT technique for water pumping system

Utilization of Solar Photo Voltaic Cell (SPVC) has significantly increased in residential, commercial, and industrial due to freely available. From the power-voltage (P–V) curve, fluctuation has been revealed over an hour because of varying irradiance, and temperature of sun rays. Maximum power point tracking (MPPT) has been essential to track power and maximize the output from SPVC constantly. In this study, a novel Improved Incremental Conductance (IIC) MPPT technique is proposed, and integrated with a boost converter to take out the maximum power from SPVC. The output power has been provided to a brushless DC motor (BLDC). Pulse Width Modulation (PWM) commutation system has been employed to control the BLDC motor through the 3-level bridge converter. The proposed study has been implemented in MATLAB/Simulink. The complete analysis has been examined at different irradiation conditions. Power consumption, loss, and efficiency have been estimated. Simulation results have been compared with conventional incremental conductance (IC). The proposed IIC MPPT has an improved 5% of tracking efficiency than conventional MPPT techniques. The results show that the effectiveness of the proposed IIC technique has attained a steady state in varying irradiation levels. In spite of the low irradiation level of 250 W/m2, the system remains effective