This paper presents a Modified Perturb & Observe (P&O) Maximum power point tracking (MPPT) algorithm using fuzzy logic-based variable step size to overcome some of the limitations associated with the conventional P&O MPPT tracking method to improve the transient response and reduce the steady-state terminal voltage oscillations. The proposed MPPT algorithm was implemented and tested on an indoor emulated PV source that is constructed from a conventional solar panel and a DC power supply, a boost DC-DC converter and a dSPACE-based MPPT controller. The advantage of implementing this testing platform for MPPT is easy implementation and indoor testing of MPPT algorithms and DC-DC power converters. Thus, dependency on atmospheric conditions such as irradiance level can be avoided. Details of the emulated PV source mathematical model and electrical characteristics, the proposed MPPT algorithm via dSPACE, simulation and test results were presented in the paper.

In this paper, Cascade PI Controller-Based Robust Model Reference Adaptive Control (MRAC) of a DC-DC boost converter is presented. Non-minimum phase behaviour of the boost converter due to right half plane zero constitutes a challenge and its non-linear dynamics complicate the control process while operating in continuous conduction mode (CCM). The proposed control scheme efficiently resolved complications and challenges by using features of cascade PI control loop in combination with properties of MRAC. The accuracy of the proposed control system’s ability to track the desired signals and regulate the plant process variables in the most beneficial and optimised way without delay and overshoot is verified using MATLAB/Simulink by applying comparative analysis with single PI and cascade PI controllers. Moreover, performance of the proposed control scheme is validated experimentally with the implementation of MATLAB/Simulink/Stateflow on dSPACE Real-time-interface (RTI) 1007 processor, DS2004 High-Speed A/D and CP4002 Timing and Digital I/O boards. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed two times with considerably improved disturbance rejection.

Temperature and temperature variation cycles of insulated gate bipolar transistors (IGBTs) are important variables for reliability assessment of inverter power module (IPM) applied in hybrid vehicles. Conventional electro-thermal (ET) simulation based on physics device model has been considered as an accurate method, but it is difficult to conduct a long real-time (over 10 min) thermal simulation as required in hybrid vehicles. In this study, a fast ET simulation model for long real-time thermal simulation of three-phase IGBT IPMs is presented in which the consideration of inverter/motor power train modelling, determination of simulation time step, calculation of temperature-dependent power losses as well as thermal network are discussed in detail. The advantage of the proposed simulation model is the IGBT temperature and variation cycle with power cycles of vehicles can be simulated at a fast speed without significant loss of accuracy. Device temperature over 10 min of real-time operation for a three-phase IGBT IPM has been simulated and validated by an experimental test.

In this paper, Proportional Gain Resonant and Gain Scheduled Proportional (PR-P) Controller based variable perturbation size real-time adaptive perturb and observe (P&O) maximum power point tracking (MPPT) algorithm is presented. The proposed control scheme resolved the drawbacks of conventional P&O MPPT method associated with the use of constant perturbation size that leads to poor transient response and high continuous steady-state oscillations. The prime objective of using the PR-P controller is to utilize inherited properties of the signal produced by the controller’s resonant path and integrate it to update best estimated perturbation that represents the working principle of extremum seeking control (ESC) to use in P&O algorithm that characterizes the overall system learning-based real time adaptive (RTA). Additionally, utilization of internal dynamics of the PR-P controller overcome the challenges namely, complexity, computational burden, implantation cost and slow tracking performance in association with commonly used soft computing intelligent systems and adaptive control strategies. The proposed control scheme is verified using MATLAB/Simulink by applying comparative analysis with PI controlled conventional P&O MPPT algorithm. Moreover, performance of the proposed control scheme is validated experimentally with the implementation of MATLAB/Simulink/Stateflow on dSPACE Real-time-interface (RTI) 1007 processor board, DS2004 A/D and CP4002 Digital I/O boards. The experimental results and analysis reveal that the proposed control strategy enhanced the tracking speed five times with reduced steady-state oscillations around maximum power point (MPP) and more than 99% energy extracting efficiency.