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In order to meet current and future emission and CO2 targets, an efficient vehicle thermal management system is one of the key factors in conventional as well as in electrified powertrains. Global vehicle simulation is already a well-established tool to support the vehicle development process. In contrast to conventional vehicles, electrified powertrains offer an additional challenge to the thermal conditioning: the durability of E-components is not only influenced by temperature peaks but also by the duration and amplitude of temperature swings as well as temperature gradients within the components during their lifetime. Keeping all components always at the preferred lowest temperature level to avoid ageing under any conditions (driving, parking, etc.) will result in very high energy consumption which is in contradiction to the efficiency targets.

The level of infotainment in today's vehicles and the customer expectation of the functionality imply a significant effort is required on thermal management of the systems, to guarantee their full operation under all operating conditions. The worst case thermal conditions the system will get exposed to are caused by solar loading on the cabin or heat up as a result of cabin heating. Simulation of a solar load driven case will be discussed in this paper. The long soak conditions during these tests result in the modelling requirement for long natural convection periods. This is creating a challenge for the conventional CFD simulations in turnaround time. New simulation methodology has resulted in significant speed up enabling these fully transient simulations in a reasonable turnaround time to enable programme support. A two phase approach to simulating this problem is proposed in this paper.

In a tiered cooling pack, the airflow through the individual heat exchangers is determined by the package and aperture lay out. Each heat exchanger rejects heat as a function of the internal coolant flows, the cooling airflow and the air temperature. In a typical automotive cooling pack, the cooling airflow will be non-uniform in velocity and temperature due to fans, aperture geometry, exterior flows, heat exchangers and recirculation. In a drive cycle, these boundary conditions will change with vehicle operating conditions like vehicle speed, engine speed, ambient temperature, and altitude. These non-uniform conditions on the cooling pack can lead to significant errors when uniform boundary conditions are assumed in a transient simulation. This error is commonly corrected using vehicle test data. A predictive approach, which eliminates the need for correlation vehicle testing, is presented.

The current trend of highly boosted petrol engines is demanding significant engineering effort on the air intake system development. The package of the air intake system is done early in the programme phase and the main engineering effort have historically been around achieving the system pressure drop targets. The thermal impact of the package is assessed during the vehicle testing phase. This can lead to significant design changes in order to maintain engine performance under all operating conditions late on in the development, driving up cost and programme delays. The highly boosted engine performance is very sensitive to heat pick up of the intake air and therefore requires an optimised system. To be able to support the engine intake design at the early program phases with thermal input, an analytical method has been developed.

Integration of advanced battery systems into the next generation of hybrid and electric vehicles will require significant design, analysis, and test efforts. One major design issue is the thermal management of the battery pack. Analysis tools are being developed that can assist in the development of battery pack thermal design and system integration. However, the breadth of thermal design issues that must be addressed requires that there are a variety of analysis tools to address them efficiently and effectively. A set of battery modeling tools has been implemented in the thermal modeling software code PowerTHERM. These tools are coupled thermal-electric models of battery behavior during current charge and discharge. In this paper we describe the three models in terms of the physics they capture, and their input data requirements. We discuss where the capabilities and limitations of each model best align with the different issues needed to be addressed by analysis.