One task of investigation and development in the automotive industry is to keep exhaust emissions within the applicable legal limits. This must be guaranteed not only during production but also during vehicle operation. In this context, thermal management of the combustion engine plays increasingly important role in the automotive industry. In addition to engine cooling, the thermodynamic and mechanical efficiency of the engine can be optimized. This leads to low fuel consumption, reduced exhaust emissions, increased performance and service life of the engine. For optimal thermal management, the individual components of the engine must be tempered as required. In this respect modelbased approaches have received considerable attention as they ensure high accuracy with a low effort to parametrize the controller. As the name suggests, such control concepts are based on component models of the respective thermal management system. In addition, the use of models of a thermal management system is not limited to model-based control strategies. In contrast, such models are applied in a variety of ways. These include, for example, the replacement of a real physical sensor with a modeled one and the diagnostic tasks during the operation of a vehicle. In this manuscript, the modeling and model-based control of a thermal management system is investigated. To this end, a low-temperature cooling circuit of a commercial vehicle is used. This cooling circuit is necessary to control the temperature of the charge air. Within the modeling task, both the hydraulic and thermodynamic models are designed. Here, the physical approaches as well as the methods based on artificial neural networks are considered. Finally, the developed models are applied as part of a model-based controller.