Energetic Optimization of an Automotive Paintshop Using Dynamic Thermo-Fluid Simulation

Abstract

The vehicle painting process is typically the most energy-intensive process within an automotive manufacturing plant. Meeting the temperature and humidity requirements during the painting application and drying stages necessitates significant energy consumption for heating and cooling in paintshops. The energy consumption of a paintshop is dynamic and heavily influenced by external factors such as weather conditions and production schedules. Consequently, it becomes a challenging task to accurately assess the energetic impact of plant modifications. This study focuses on optimizing an automotive paintshop through the application of a validated dynamic model of the facility. The dynamic model is implemented using Modelica and captures main painting processes such as pre-treatment, drying ovens and HVAC units. The model is calibrated using transient data collected from the actual plant. A wide range of energy optimization strategies is presented, encompassing improvements in heat recovery, airflow management, and control systems. The energy saving potential of each measure is estimated using the dynamic model by simulating the model for one typical year. The results indicate that these measures can reduce energy demand significantly: A shift to a three-shift schedule lowers energy demand per vehicle by 10.4%. Integrating a heat pump into pre-treatment and e-coat processes achieves a combined COP of 5.12. Additionally, optimizing an air supply unit's controller decreases its annual energy demand by 46.5%.