Predictive under Hood Thermal Management Model Ashok Leyland Technical Center

Format:

Book

Conference/Event

Author/Creator:

P V, Navaneeth, author.

Contributor:

ML, Sankar

Prasad, Suryanarayana A N.

Conference Name:

Symposium on International Automotive Technology (2024-01-23 : Pune, India)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2024

Summary:

In the automotive industry, thermal management plays a very important role to solve the problems of energy saving and emission. The under hood thermal management is one of the critical aspects in vehicle thermal management since it caters to critical aspects of engine cooling, charge air cooling, air conditioning and turbocharger cooling. The appropriate thermal management of these critical components is necessary for ensuring the appropriate performance by the vehicle. Hence, under-hood thermal management is the core of the integrated vehicle thermal management.In the thermal management analysis approaches, the numerical simulation is widely adopted as an important approach. Hence, in this paper a model is developed in MATLAB to handle 1D parametric analysis of the cooling system, while reducing the testing time and resources taken for the product development. The developed model can be used to evaluate multiple aggregate options for CAC, Radiator, Engine, Fan et cetera The model predicts the Limiting Ambient Temperature (LAT), Inlet Manifold Temperature Difference (IMTD), External air flow rate, Inlet and Outlet temperatures of Air and Coolant at each aggregates using the characteristics of each aggregates (radiator, CAC, coolant pump, engine et cetera) as the input.The 1D model is capable of predicting the change in performance of the cooling system with change in position of the components relative to one another. The performance of the cooling system can be predicted for different combinations of cab, radiator, charge air cooler (CAC), engine. The model can minimize the usage of resource intensive and expensive CFD and provide results in a few minutes. Moreover, the developed model has better predictive capability compared to KULI, a 0D simulation widely used in industry. The model predictions compared fairly accurately with physical test data

Notes:

Vendor supplied data

Publisher Number:

2024-26-0272

Access Restriction:

Restricted for use by site license