Permanent magnet synchronous machine is widely used for electric vehicles traction because of its high power density and its efficiency on a large flux weakening range. This paper focuses in particular on the estimation of PMSM parameters using EKF, we present a study assessing the temperature variations impact on the behavior of PMSM motor, and therefore we propose to estimate the temperature-dependent parameters. The main contribution in this work is an effective method for estimating parameters or their temperature variation, makes it possible to study and to avoid performance degradation by tracking and adapting the parameters in torque observer in order to find the same performance at any temperature and can be also used for thermal monitoring, which allows for better availability of motor, without causing damage, however, the knowledge of degradation mechanisms also gives insight for the design of this machine. Nowadays, there are essentially maps of reference currents according to the torque and speed that are used by car manufacturers and no account is then given of the parameter variations. The effectiveness of the proposed estimation method verified by both simulation and experiment.

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In this paper, we focus on the design, modeling and implementation of a MPPT controller based maximum power tracking of photovoltaic system. The electrical characteristic of The PV system is non-linear and changes with the solar irradiation and the ambient temperature. Therefore, the incremental conductance (IC) method control is known for its stability and robustness, and is used to extract the maximum energy from the PV source using a boost converter topology. It provides a strong basis for the improvement and optimization of control parameters of a photovoltaic system. Implementing MPPT algorithm usually need the use of a lot of sensors if accuracy of the system has to be increased. However, IC method with an extended Kalman filter (EKF) can be utilized in order to estimate some parameters to reduce the number of Sensors. The EKF is deployed in the optimal position to estimate both current and the capacitor voltage, thus allowing to eliminate two sensors devise from the entire PV system, which increases the system efficiency and reliability, simplifies the control method and decreases the system cost. The performance of the proposed technique is validated by experimental and simulation results under different operating conditions and load changes.

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