Contents lists available at ScienceDirect Solar Energy journal homepage: www.elsevier.com/locate/solener Design and verification of photovoltaic MPPT algorithm as an automotive- based embedded software Youssef Cheddadi ⁎ , Fatima Errahimi, Es-sbai Najia Sidi Mohamed Ben Abdellah University, Laboratory of Renewables Energy and Intelligent Systems, Road Imouzzer, BP 2202, Fez, Morocco ARTICLE INFO Keywords: Embedded software Validation and verification MPPT Model-based design Software in the loop Processor-in-the-loop ABSTRACT This paper presents the design and verification process of the Maximum Power Point Tracking Controller in accordance with the automotive development process standards, which could be used in Photovoltaic charging stations or in on-board chargers of electric vehicles. Considered as an automotive embedded software, the de- signed MPPT controller follows a sequence of three tests of the Model-based design MBD Approach to be verified and validated. The ultimate aim is to present a road map to design, test and validate an embedded software of the MPPT algorithm in vehicle based software. We design a modified Perturb and Observe P&O algorithm, then we generate optimized C code for a 32 bit ARM cortex microcontroller. Next, the algorithm is simulated through Model-in-the loop MIL, Software-in-the loop SIL, and finally co-simulated through Processor-in-the-loop PIL technique in the low cost STM32F429 discovery development board. During all the different tests, the designed embedded software shows a high accordance with MPPT requirement and high performances. 1. Introduction Combining electric vehicles and renewable energy is considered a vital and sustainable solution for both transport and power generation issues. Furthermore, we find numerous common points and intersec- tions between the two sectors, namely the solar vehicles, the electrical and hybrid-electrical vehicles that use photovoltaic modules (PV) as on- board or off-board charger for their batteries(Bhatti et al., 2016; Chellaswamy and Ramesh, 2017). The intermittent nature of photovoltaic power depends strongly on weather conditions. Consequently, the variation in either solar irra- diance or temperature results in nonlinear power characteristics (Cheddadi et al., 2017), which makes the position of the Maximum Power Point (MPP) variable over time and difficult to be located and tracked. In the literature, researchers have tried to solve this challenge for a long time by proposing numerous techniques that could increase the efficiency and the harvested power from a photovoltaic system. These techniques are called maximum power point tracking (MPPT) algorithms(Ahmed and Salam, 2015; Li et al., 2017). In fact, various MPPT approaches have been developed in the literature. These techniques could be divided into intelligent and classical strategies. In the first category we find: Fuzzy Logic, Neural Network, Extremum seeking control and Particle swarm optimization (Brunton et al., 2010; Chiu, 2010; Gavhane et al., 2017; Sahnoun et al., 2013; Vengatesh and Rajan, 2016). In the second category we find Incremental Conductance Perturbation, Frac- tional Open-Circuit Voltage, and the most widely used technique Perturb and Observe (P&O) algorithms. The P&O technique is popular due to its simplicity and fast response (Ahmed and Salam, 2015; Li et al., 2017; Sera et al., 2013). Researchers in previous studies have worked to improve the PV system efficiency. However, they do not follow any standard to develop reliable software dedicated to control their converters, especially in the applications that integrate solar vehicles and solar charging infrastructure for electric vehicles(Tong et al., 2013; Youssef et al., 2018). On the other hand, Carmakers and third-suppliers of electrical and/or electronic systems working in automobiles production, follow various strict standards and norms required in the automotive sector, namely ISO 26262 Standards for functional safety (Hommes, 2012), This is not only because of the highly critical nature that automotive applications present for human life; but also in order to accelerate the product development process, increase its quality and make traceability in order to reduce the time to market then decrease the total production cost. In this paper, one of the most widespread MPPT techniques, Perturb & Observe (P&O) is investigated in its modified version, tested and validated following the Model-based design (MBD) approach, which is https://doi.org/10.1016/j.solener.2018.06.085 Received 15 March 2018; Received in revised form 1 June 2018; Accepted 21 June 2018 ⁎ Corresponding author. E-mail address: Youssef.cheddadi@usmba.ac.ma (Y. Cheddadi). Acronyms: ECU, electronic control unit; IDE, integrated development environment; MBD, model-based design; MIL, model in the loop; MPPT, maximum power point tracking; P & O, perturb and observe; PIL, processor in the loop; PV, photovoltaic; PWM, pulse width modulation; SDK, software development kit; SIL, software in the loop; V & V, verification and validation Solar Energy 171 (2018) 414–425 Available online 03 July 2018 0038-092X/ © 2018 Elsevier Ltd. All rights reserved. T