Thermoelectric generator is a device that consists of semiconductor material which can directly convert the thermal energy heat from sources like waste heat, geothermal energy or solar energy into DC electrical energy, depending on the Seebeck effect. In this paper a simple and accurate TEG model is proposed to achieve the electrical characteristics of the TEG module and maximize the electrical output power at various operating conditions. Incremental conductance (INC) algorithm with DC-to-DC boost converter is proposed in this study to track the maximum output power point (MPP) of the TEG module. The complete system including the TEG model and DC-to-DC boost converter with INC-MPPT control algorithm is simulated using MATLAB/Simulink software and implemented with Arduino microcontroller at constant and variable temperature on the both sides of the TEG module. Then, the overall tracking performance of INC-MPPT is analyzed. Finally, simulation and experimental results are compared with manufacturing data sheet of the real TEG module used in this study and reveal that the proposed TEG testing and simulation model are achieved the electrical characteristics and maximized the electrical output power of the TEG module at constant and variable temperature with a good accuracy and faster response to track the MPP at a rapid change of temperature on both sides of the module.

Thermoelectric Generator (TEG) is a new trend in renewable energy issues that utilize heat energy to produce electricity from various waste energy sources. These sources are available from natural sources like geothermal and solar heat and recovering from many industrial processes. In this paper, the electrical performance of a TEG system has been analyzed when the Incremental Conductance - maximum power point tracker (INC-MPPT) control algorithm has been applied to maximize the energy conversion efficiency. The TEG system has been simulated, implemented and tested at different values of temperature difference. Simulation and experimental results show that, the proposed control algorithm can be operated at the maximum power point (MPP) of the TEG module at any operating condition with good accuracy and low fluctuation around this point. Also, the experimental results show that, the harvested power has been duplicated by more than six times by applying the INC-MPPT algorithm (11.9W) in comparing with connection without MPPT (1.9W) at the same resistive load (16Ω), the same applied temperature and the same operating conditions.

Interior rotor axial flux permanent magnet synchronous motor (IRAFSM) sensorless control is essential to inject the motor inside the electric vehicles’ tire. The proposed straight-line guided by the reference speed (SLGBRS) sensorless space vector pulse width modulation (SVPWM) inverter-direct torque control (DTC) technique for driving the IRAFSM used for electric vehicles (EVs) is evaluated using laboratory emulator setup. A hardware-in-the-loop (HIL) controller and data acquisition are used as a real-time emulation, while the results are compared with MATLAB simulation results. Both simulation and real-time application of the proposed sensorless control for the IRAFSM offer a good speed response. The results of real-time evaluation are identical with the simulation results so, the control is accurate and suitable for practical applications. Urban dynamometer driving cycle (UDDS) for heavy-duty vehicles is used as a driving cycle for simulation and real time evaluation. UDDS is used to ensure the reliability of the proposed control against a wide range of speed changes to be applicable for many applications. The proposed technique allows utilizing the IRAFSM in many applications that requires less contact and reduced sensors like robotics and inside EV’s tire with a good reliable control.