Development of the control algorithm for a retrofit reconversion kit

The automotive industry faces a complex challenge: navigating fierce competition, evolving standards, and increasingly complex components while tackling sustainability concerns. Global pollution and climate change demand solutions, and electrification via Battery Electric Vehi- cles (BEVs) offers a promising path to carbon neutrality. However, full adoption faces hurdles like higher initial costs and the not readiness of the infrastructure and of the supply chain of component and subsystems providers. This is where the groundbreaking project, called “EV- ERGRIN”, advanced by “brain Technologies S.r.l.” comes in. The general project proposal of the company is to develop an electronic device, a vehicle management unit (VMU), a smart device that permits rapid configuration of a new electric vehicle, but can also be adapted to an existing vehicle, as part of a "retrofit" activity, i.e. the conversion of a polluting conventional vehicle into a pure electric one allowing a considerable cut in the total cost. This thesis is part of this ambitious company project, and it is made up of three parts: firstly, an overview of the “EVERGRIN” project with details and insights will be provided, followed by an examination of relevant theories related to the automotive standards, V-cycle, Model-In-The-Loop (MIL) phase and software testing; then, the operational part that was carried out for this thesis work will be exposed and illustrated step by step; starting from the writing of the system requirements, in accordance with the current regulations in the industry (e.g. ISO/IEC/IEEE 29148:2018); afterwards, the definition of the general state machine describing the most significant macro conditions assumed by a BEV during its various operating phases, with a focus on the de- velopment process and iterations, will be discussed; lastly, everything will be translated into software using Model-based software design (MBSD) techniques using Simulink and Stateflow environments for the creation of an interactive and real-time simulation adjustable during the execution from a custom-made dashboard. Following a thorough analysis and discussion of the data, a final and comprehensive consideration tailored towards future applications will be provided.