# Modeling and Control Simulation of Power Converters in Automotive Applications
## 1 Introduction  
### Motivations  
In recent years, the commercial panorama of electrified cars has experienced unparalleled growth. The increasing need for extremely efficient electric and hybrid cars is a modern challenge that is driving important advances in science. It is noteworthy that the creation of resilient electronic power flow systems has become a central area of interest for innovation [1, 2]. For a variety of compelling reasons, it is crucial to use mathematical models and run simulations when designing in-vehicle electronics systems, such as power electronics, onboard mechatronics, electric drives, and power electronics. Design optimization: Using mathematical models and simulations, it is possible to assess several design configurations and choose the most promising one that will provide optimal performance in terms of effectiveness, dependability, and durability over an extended period of time. This approach can prevent expensive design mistakes and shorten the time needed to produce a product from start to finish [3, 4]. Cost reduction: The adoption of mathematical models and simulations obviates the necessity of creating physical prototypes to test various design setups. Consequently, this leads to a substantial reduction in product development costs and expedites the time required to bring the product to the market [5; 6; 7]. Performance improvement: Power electronic converters may have their performance carefully assessed under a range of operating situations, including variations in temperature or load, by using mathematical models and simulations. This makes it possible to adjust converter control and guarantees top performance in a variety of operating conditions [8]. Safety assurance: Through the use of mathematical models and simulations, it is possible to evaluate power electronic converter behavior in the event of overload or failure. This opens the door for the installation of strong defenses, guaranteeing the security of both drivers and passengers [9; 10; 11; 12; 13; 14]. The use of mathematical models and a model-based design (MBD) approach is essential to increase the performance of power electronic systems and to analyze the solution space, including studying the effects of the variation of circuit parameters, the effects of choices and simplified hypotheses in the design, and the robustness of control algorithms [15; 16] against unwanted effects such as measurement noise or transduction errors [17; 18]. In the literature, there are many concrete examples of the development and analysis of power electronic systems and electric drives for automotive applications and the mechatronics industry. For example, the authors of [19; 20] use the MBD approach very extensively to improve the performance of the control of electric drives in the presence of the Cogging effect, analyzing the robustness and profiling the computational complexity in simulation. In [21; 22], an analysis of the computational complexity of advanced control algorithms for power electronic systems based on SW MBD tools is proposed to ensure integration with real-time constraints in embedded platforms. In [23; 24; 25; 26], the use of the MBD approach for the design and integration of mechatronic systems up to the implementation phases is proposed. In other works, the authors show how to use MBD and simulation environments massively, to compensate for the lack of experimental data and address battery health estimation problems. Works such as [27] show how simulations can create scalable models of SiC/GaN devices not yet on the market, combining experimental characterization measurements of such devices with complex and scalable models, to be integrated into more complex electronic systems. Essentially, the use of mathematical models and simulations in power electronic converter designs for automotive applications helps to ensure the highest level of user and vehicle safety while also improving product performance and reducing development costs [28; 29; 30; 31].