Developing Intelligent Windshield Fogging Prediction and HVAC Control Model

2022-28-0460

11/09/2022

Features
Event
SAENIS TTTMS Thermal Management Systems Conference-2022
Authors Abstract
Content
The Indian continental region encompasses various geographical terrains and climatic conditions, which necessitates automotive OEMs to build robust cabin climate control systems that ensure year round occupant comfort. Such systems comprise of, an on-board Heating Ventilation Air Conditioning (HVAC) sub-system and a control head (manual or automatic) that works as a user interface for adjusting parameters such as airflow, temperature and air directivity best suited to the occupants. In case of passenger cars, the on board HVAC system primarily serves two major purposes. To provide year round thermal comfort to the passengers and to enable defogging and defrosting action of front and rear windshield as per regulatory requirements and customer needs particularly for enhancing visibility in cold and humid ambient conditions.
Currently, Full Automatic Temperature Control (FATC) control heads have been introduced in nearly all segments of passenger cars, particularly in the top end models It intelligently manages the HVAC system to meet varying customer comfort requirements by deployment of sensors at various locations and servo motors on the under dash unit. In spite of this automation, there continue to be instances wherein windshield defogging function is not fully automatized and needs to be periodically activated by pressing a switch. The case of repetitive and recurring unclear front vision severely affects driving safety of the occupants.
This present body of work prospects upgrading the FATC system in a manner such that, the chances of fogging over the windshield is judged and necessary defogging action is enabled through an automatic control model.
The predictive algorithm is based on input signals of relative humidity and glass temperature at defined locations over the windshield. Further, the various dominant factors affecting chances of windshield fogging are impressed in the prediction model to evaluate real time occurrence of fogging. The control model will then adjust various HVAC operating states such as blower speed, air recirculation, air distribution and cooling/heating effect as and when the chances of fogging is predicted. Such controlled operation of HVAC system acts as mean of additional active safety feature. It also beneficial for improving driving range of vehicle. The integrated HVAC system and control model is tested under different ambient conditions, occupant load using climate wind tunnel, and on-road drive scenario. The evaluated climate control system performance shows that integrated model worked well to ensure optimum human comfort and driving safety.
Meta TagsDetails
DOI
https://doi.org/10.4271/2022-28-0460
Pages
7
Citation
Venu, S., Mehta, B., and Panchare, D., "Developing Intelligent Windshield Fogging Prediction and HVAC Control Model," SAE Technical Paper 2022-28-0460, 2022, https://doi.org/10.4271/2022-28-0460.
Additional Details
Publisher
Published
Nov 9, 2022
Product Code
2022-28-0460
Content Type
Technical Paper
Language
English