This paper presents guidelines to develop the Maximum Power Point Tracking controller, as developed in the automotive and aeronautical applications, this by following the V-cycle development process, which means that our controller will be validated by using Model In the Loop/ Software In the Loop/Processor In the Loop tests. In order to have the possibility of integrating the MPPT embedded software in automotive and aeronautical areas, and on the other hand to propose a low-cost option to test the hardware implementation of the MPPT algorithm. Therefore, a modified variable step Incremental Conductance algorithm is proposed in this study, which can reduce the steady-state oscillations and increase the tracking speed under sudden irradiance variation. Then, the Model-based design of the modified algorithm is developed and connected to the plant model (photovoltaic panel and Boost converter). Next, the system model is tested and validated by using Model In the Loop process. After that, the software of this algorithm is automatically generated for the host computer using embedded coder tool, and this software is connected to the plant model and tested using Software in the Loop process in the host computer. Finally, the software is generated from the MPPT model for the STM32F4 discovery board in order to create the Processor In the Loop block, which will be run in the STM32F4 discovery board, and the plant model will be simulated in the host computer, and the ST-LINK communication is used in order to connect the host computer and the embedded board.

This paper presents the design and practical implementation of a simple active dual‐axis solar tracker (DAST) to track the sun's movement by using fewer components and low‐cost as well. A dual‐axis mechanism is developed in order to tilt the PV panel by two servo motors facing the highest intensity of sunlight captured by LDR sensors, which are placed in the four corners of PV panel. The DAST prototype was constructed practically and tested using a real‐time virtual instrument based on Excel to determine its efficiency. Moreover, a comparison based on experimental results between the energy produced by the proposed smart DAST and a fixed panel shows that the smart DAST produces 36.26% more energy compared to the fixed panel. The proposed active DAST can be easily implemented without possessing deep knowledge about solar tracking technologies and electronic engineering.

Photovoltaic (PV) systems based on multistring configuration are the best effective solution, given its advantages in terms of system availability, reliability, and energy efficiency. In this particular configuration each substring has its own dc–dc converter and a dedicated maximum power search algorithm which increase the cost and complexity. In this article, an efficient centralized global maximum power tracking (GMPPT) algorithm for multistring PV array subject to partial shading conditions is proposed. The algorithm is based on artificial bee colony (ABC) as an optimization approach to provide the optimal duty cycles allowing the extraction of the optimal global maximum power from each substring. In particular, the proposed approach allows significant reduction of the required sensors to only one pair of current and voltage sensors, at the common point of connection of the overall PV strings. The simulation study has been carried out under Cadence/Pspice and MATLAB/Simulink platforms on the I–V curves to confirm the effectiveness of the proposed algorithm when several shading patterns occur. In addition, complex shading pattern of a daily profile has been also carried out to demonstrate the GMPPT finding in dynamically variable conditions. Performance comparison against particle swarm optimization based maximum power point tracking algorithm and the traditional perturb and observe method has also been carried out. The obtained simulation and experimental results have shown the effectiveness and a good tracking capability of the proposed ABC algorithm in a multistring PV array configuration under uniform and nonuniform irradiance.

Internet of Vehicles (IoV) is a new concept, derived from combining VANET and Internet of Things (IoT), aiming at increasing road’ user safety and reducing the number of accidents. In IoV, different types of communication are possible, namely, vehicle-to-sensor, as the car is considered as a powerful multisensory object, vehicle-to-pedestrian i.e. sharing data between vehicle and people, and vehicle-to-cloud communication in which cloud data centers and vehicles are the main actors. Indeed, the IoV’s topology is very dynamic and non-uniform; it can be a target of several types of attacks that could menace people’s lives. This paper is a detailed review of the internet of vehicles by presenting first of all the VANET networks including their different components, their possible communication, and their applications. The reasons behind the transition from VANET to IoV are also carried out in this review. After this, an in-depth study of IoV is being done by discussing its architecture and the different sensors and network protocols used in IoV. As it is not standardized, a comparison of the existing architecture is also elaborated in this review. Taking into account its importance, we devoted a part of this work to the security aspect for IoV by presenting the security requirements and the possible attacks, moreover, a study of the proposed security solutions will be done

The real implementation of the maximum power point tracking (MPPT) controllers for the photovoltaic (PV) systems is still a big challenge for researchers working in this field. Often, they use simulation tools to assess the performance of their MPPT algorithms before actual implementation. In this context, this paper aims to propose a trusted simulation of a PV system designed under Proteus software. The proposed PV simulator can be used to verify and evaluate the performance of MPPT algorithms with a closer approximation to the real implementation. The main advantage of this model that it contains a real microcontroller, as can be found in reality, so that same code for the MPPT algorithm used in the simulation will be used in real implementation. In contrast, when using (Powersim Software) PSIM or Matlab/Simulink, the code of the algorithm must be rewritten once the real experiment begins, because these tools don’t provide a microcontroller or an electronic board in which our algorithm can be implemented and tested in the same way as the real experiment. After this section, a modified Hill-Climbing (HC) algorithm is introduced. The proposed algorithm can avoid the drift problem posed by conventional HC under a fast variation in insolation. The simulation results show that this method presents good performance in terms of efficiency (99.21%) and response time (10 ms), which improved by 1.2% and 70 ms respectively compared to the conventional HC algorithm.