1 option
Development of a Software Algorithm Based Semi-Automated Data Acquisition System for Gasoline Vehicle Calibration on Chassis Dynamometer Tata Motors, Limited
- Format:
- Book
- Conference/Event
- Author/Creator:
- Kavekar, Pratap Chandrashekhar, author.
- Conference Name:
- Symposium on International Automotive Technology (2026) (2026-01-28 : Pune, India)
- Language:
- English
- Physical Description:
- 1 online resource cm
- Place of Publication:
- Warrendale, PA SAE International 2026
- Summary:
- Vehicle level EMS tuning is one of the crucial parts of calibration development. In this, vehicle level data is collected by using chassis dynamometer. Main objective of this data collection is to log the engine and vehicle level parameters at various speed and load conditions, covering the entire engine operational zone. This data acquisition process includes verification of base calibration, transient calibration and emissions-related calibration. Due to multiple number of similar acquisition steps this process becomes repetitive in nature and it covers 30-40% of the total calibration duration. All these measurements follow a standardized and repetitive sequence. However, these tasks are predominantly performed manually, leading to potential human error and fatigue.This paper presents a novel and comprehensive algorithm developed using INCA FLOW software; the first of its kind for this application. Here, a systematic development approach is used. First, the crucial vehicle data acquisition activities are identified. Then these activities are mapped into detailed steps. In this paper, an algorithm is proposed which introduces a semi-automated, stepwise process for data acquisition during chassis dynamometer testing, thus significantly reducing the manual intervention. In order to take of the safety conditions, arising due to possible failure modes of failure, safety-monitoring conditions are also introduced. These failures are mainly due to thermal and mechanical limits of the engine, vehicle and human safety while testing. Additionally, a sophisticated data processing algorithm has been designed to significantly reduce manual intervention, improve data accuracy, and streamline the overall calibration development timeline
- Notes:
- Vendor supplied data
- Publisher Number:
- 2026-26-0535
- Access Restriction:
- Restricted for use by site license
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.