Some suggest that autonomous driving is the ultimate example of the implementation of the Internet of Things. An integral integration of internal and external sensors working together to create an evolutionary change in the way people use transportation. There are two additional layers of complication to designing for vehicles, one the impact of application failure can be significant and two vehicles have an extensive need for sensors, signal processing elements, and image recognition engines. As manufacturers continue to add more advanced sensors, high-resolution displays, on-vehicle cameras, black-box storage and vehicle-to-vehicle (V2V) communications, cars will need accelerated processing power and increased data storage capacity to enable this connectivity. The initial applications for IoT in automotive are:
- Over the Air (OTA) Updates – The ability to update navigation and system software wirelessly and securely. Already implemented in some high-end models, like Tesla, this allows real time updates, removing system vulnerabilities and ensuring critical safety updates are implemented.
- Vehicle to Vehicle (V2V) – The ability of cars to communicate with one another to improve traffic flow and reduce congestion as well as making the roadways safer.
- Vehicle to Infrastructure (V2I) – The ability of cars to communicate with the infrastructure around them to improve traffic flow and commute times. This information fed through advanced algorithms enabling advancements in traffic signals and determining the optimal speed for the IoT connected cars on the roadway.
To enable the IoT in Automotive, new system level technology is needed. Along with microprocessors and computing power, innovative memory is a key element to the success of IoT in automobiles. Memory is used to store code and data and to run programs for infotainment systems, the electronics in the dashboard, the control units of the engine and for Advanced Driver Assistance Systems (ADAS). Those systems build the basis for future self-driving cars. For today's automotive memory solutions, high temperature and quality standards are key. Connected car applications require specific memory solutions due to the stringent quality, reliability, and operating temperature requirements of the automotive market. One additional key component that is becoming a basis for many IoT devices and especially automotive is the grounds up development of enhanced security solutions, contributing towards protecting the code in systems and providing a foundation for identity for future autonomous services.
Not only are performance increases and more advanced systems driving this, but the relative location of the memory pushes the boundaries. Think of the forward looking camera right behind the windshield with no airflow and the sun beating down on it during a hot Texas summer. Combine that with the proximity to the processor and the memory quickly heats above the 105ºC range quickly pushing towards 125ºC. The automotive market's unique set of feature requirements include:
- Striving Towards Zero Defect Approach – Targeting no failures over the product lifecycle to ASIL standards
- Automotive-Grade Selection – Strict selection criteria in fabrication, assembly, and test to ensure the highest quality product
- Burn-In Flow – Simulating the first year of product life to improve overall quality, which is statistically when marginal products fail
- Automotive Certification of Fab and Assembly Sites – Fab and assembly roadmap certification to ISO/TS 16949 and ISO262
- AEC-Q100 – A failure mechanism-based stress test qualification for integrated circuits
Micron is the leading memory provider to the automotive industry (source: Gartner 2015). Visit our Automotive Solutions page to learn more about our commitment to this industry.