Performance Investigation of Air Conditioning System in Electric Vehicle by Fault Detection and Diagnosis Bosch Global Software

Format:

Book

Conference/Event

Author/Creator:

Bezbaruah, Puja, author.

Contributor:

Pilakkattu, Deepak

Yadav, Ankit

Conference Name:

SAENIS TTTMS Thermal Management Systems Conference (2025-11-06 : Guwahati, India)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2025

Summary:

The study emphasizes on detection of different faults and refrigerant leakage as well as performance investigation of automobile air conditioning system for an electric vehicle by varying various operating conditions. A refrigerant leak in an EV isn't just an inconvenience; it's a potential threat to vehicle range and usability, lifespan and health of the expensive battery pack, overall vehicle performance, passenger safety and comfort, component longevity (motor, power electronics), environmental responsibility.Due to the refrigerant leakage, the cooling system performance degrades, and components tend to fail. Because of that this study is focusing on deriving an algorithm to have an early detection of fault and leakage in the vehicle. The performance of the system is predicted for actual conditions of operation encountered by the automobile air conditioning system. The objective of the present work includes predicting the causes and effects of refrigerant leakage in AC system of Electric vehicle, developing numerical simulation model of the air conditioning system and an algorithm to detect different faults and predict the performance with and without leakage which uses the refrigerant R134a. For this purpose, a simulation model and a leak detection algorithm have been developed for a small automobile air conditioning system with R134a refrigerant.The Coefficient of Performance (COP), cooling capacity values are compared for both with and without refrigerant leakage in the AC system. For that, the temperature and pressure values of different points from the simulation model of the AC system are taken and used by the algorithm in stateflow model to detect the leakage in the system. After the complete analysis it has been noticed that the COP of the AC system drops significantly from 4.7 with 0% fault to 3.59 with 66% fault, and cooling capacity drops from 1.398kW with 0% fault to 0.46kW with 66% fault, which indicates the deterioration of the system over time

Notes:

Vendor supplied data

Publisher Number:

2025-28-0353

Access Restriction:

Restricted for use by site license