Search Results

Thermal development of automotive applications is a lot more complex than it used to be in the past. Specifically, for Plug-in Hybrid Electric Vehicles (PHEVs), all the sub-systems are so intertwined that it’s hard to analyze them as sub-systems only. A system level solution is needed for proper sizing of components. For early thermal development, a co-simulation method can ensure that we take into account the inter-dependency of all the thermal features in the car. As for example, a large PHEV battery may need to be passively cooled by refrigerant, which is also associated with the interior Heating, Ventilation, and Air Conditioning (HVAC) cooling system. For proper sizing of the condenser, chiller etc., one has to account for the battery cooling and cabin cooling as one system. There are also many thermal actuators on a PHEV, e.g. control valves, pulse-width-module (PWM) pumps, electric compressor, electric coolant heaters etc.

Automotive thermal systems are becoming complicated each year. The powertrain efficiency improvement initiatives are driving transmission and engine oil heaters into coolant network design alternatives. The initiatives of electrified and autonomous vehicles are making coolant networks even more complex. The coolant networks these days have many heat exchangers, electric water pumps and valves, apart from typical radiators, thermostat and heater core. Some of these heat exchangers, including cabin heaters deal with very small amount of coolant flow rates at different ambient conditions. This paper describes how viscosity can be a major reason for simulation inaccuracy, and how to deal with it for each component in the coolant network. Both experimental and computational aspects have been considered in this paper with wide range of ambient temperatures.

In this paper, the development of a transient thermal analysis model for the exhaust system is presented. Given the exhaust gas temperature out of the engine, a software tool has been developed to predict changes in exhaust gas temperature and exhaust surface temperature under various operating conditions. The software is a thermal solver that will predict exhaust gas and wall surface temperatures by modeling all heat transfer paths in the exhaust system which includes multi-dimensional conduction, internal forced/natural convection, external forced/natural convection, and radiation. The analysis approach involves the breaking down of the thermal system into multiple components, which include the exhaust system (manifold, takedown pipe, tailpipe, etc.), catalytic converter, DPF (diesel particulate filter), if they exist, thermal shields, etc. All components are modeled as 1D porous and 1D non-porous flow streams with 3D wall layers (solid and air gaps).

This paper discusses simplified lumped parameter thermal modeling of power train components. In particular, it discusses the tradeoff between model complexity and the ability to correlate the predicted temperatures and flow rates with measured data. The benefits and problems associated with using a three lumped mass model are explained and the value of this simpler model is promoted. The process for correlation and optimization using modern software tools is explained. Examples of models for engines and transmissions are illustrated along with their predictive abilities over typical driving cycles.