Extracting Electronic Crash Data from Damaged Event Data Recorders Using Three-Dimensional Printing Techniques – A Non-Destructive Retrieval Method

2022-01-1013

03/29/2022

Event
WCX SAE World Congress Experience
Authors Abstract
Content
As a result of fire damage or other trauma, electronic crash data recorded to an airbag control module’s (ACM) memory may be inaccessible by traditional imaging. These methods include traditional imaging through a vehicle’s diagnostic link connector (DLC) or accessing the electronic crash data directly through the ACM. Previous literature explored destructive and non-destructive methods to recover electronic crash data from ACMs containing eight-pin small outline integrated circuits (SOIC8) electronically erasable programmable read-only memory (EEPROM). The non-destructive methods described in previous literature can be applied to modules containing SOIC8 storage devices but cannot be applied to more complex multipurpose memory chips due to their unique design, smaller spacing between pins, and the significant increase in pin count. With the advancement of automotive technology, our vehicles are becoming more connected and more automated, resulting in the need for more advanced microprocessing power and more advanced data storage solutions. With the advancements of technology and the complexity of the ACMs, it is not uncommon to see modules with memory storage contained within complex chips with 64-pins and even 100-pins. This paper explores and validates non-destructive three-dimensional printing methods for dealing with complex memory storage devices, for the extraction of electronic crash data from damaged ACMs through alternative methods while following the groundwork of previous approved methodology.
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Citation
Zeitler, J., and Wilson, P., "Extracting Electronic Crash Data from Damaged Event Data Recorders Using Three-Dimensional Printing Techniques – A Non-Destructive Retrieval Method ," SAE Technical Paper 2022-01-1013, 2022, .
Additional Details
Publisher
Published
Mar 29, 2022
Product Code
2022-01-1013
Content Type
Technical Paper
Language
English