Accelerate Automotive Applications with FPGAs
Discover how FPGA's flexibility and performance efficiency are reshaping automotive and transportation landscapes, driving future mobility innovations and infrastructure advancements.
FPGA Technology in Automotive
With rapidly evolving standards and requirements for Advanced Driver-Assist Systems (ADAS) and In-Vehicle Experience (IVE) applications, the need for flexibility and faster development cycles while maintaining a high performance-per-watt is the primary concern for system designers. By combining reprogrammable FPGAs with an expanding range of automotive-grade products, FPGAs enable automotive engineers to meet their design requirements and stay ahead in an evolving industry.
Benefits of FPGA in Automotive
Efficient Real-Time Processing
FPGAs enhance automotive applications through parallel processing, low latency, and customizable designs, making them suitable for sensor fusion. They enable efficient real-time data processing, reduce energy consumption through dynamic reconfiguration, and effectively balance performance with efficiency, which are essential for systems like ADAS and autonomous driving.
Safety and Security
FPGAs offer adaptable hardware for automotive safety and security, featuring low-latency processing, functional isolation, and redundancy. They enhance security with customizable encryption and real-time cryptographic processing, making systems resilient against threats while ensuring compliance with standards like ISO 26262 and ISO/SAE 21434 for long-term protection.
Customization and Scalability
FPGAs enhance automotive applications through parallel processing, low latency, and customizable designs, making them suitable for sensor fusion. They enable efficient real-time data processing, reduce energy consumption through dynamic reconfiguration, and effectively balance performance with efficiency, which are essential for systems like ADAS and autonomous driving.
Future-Proofing and Innovation
Embracing FPGA technology future-proofs automotive and transportation solutions by supporting evolving standards and emerging technologies. From 5G connectivity to AI-driven analytics, FPGAs enable continuous innovation in vehicle automation, smart mobility, and sustainable transportation initiatives, ensuring competitiveness and relevance in dynamic markets.
The Future of AI in Automotive
AI is transforming the driving experience by enabling advanced capabilities which make vehicles smarter, safer, more efficient, reliable, enjoyable and easier to operate. Field Programmable Gate Arrays (FPGAs) and FPGA-based SoCs are uniquely suited to accelerate these AI-driven tasks because they provide efficient performance, adaptability and energy efficiency. Altera FPGAs have specialized AI capabilities embedded within the logic fabric to accelerate AI workloads. The revolutionary addition of AI Tensors to the traditional FPGA DSP block enables support for AI applications with high-performance vector and matrix operations in a scalable, resource and power efficient FPGA device.
Sensor processing and fusion
In order to make vehicles safer and easier to operate, the automotive industry is seeing a dramatic proliferation of cameras and other types of sensors, such as LiDAR, RADAR and motion sensors around the vehicle and within the cockpit. Altera FPGAs and SoCs have specialized, AI-enabled Digital Signal Processors (DSPs), embedded throughout their logic fabric, which can be used to perform the demanding matrix multiplication tasks required by AI. These AI-enabled DSPs allow for very fast and efficient processing and fusion of sensor data so that it can consumed efficiently by the central brain of the car, making the vehicle smarter and safer.
Driver and occupant monitoring and voice controls
AI-enabled FPGAs can be used by camera systems and sensors within the cabin of the vehicle to identify drivers and occupants and to monitor driver behavior as well as occupant safety and comfort. AI-driven analysis of driving behavior can be used to alert the driver of potentially hazardous driving behavior, predict and prevent potential mishaps, and even allow the vehicle to take preventative actions to avoid a collision. In addition, AI can be used to implement very fast and highly accurate AI-based voice recognition algorithms to allow drivers and passengers to safely and easily interact with the vehicle.
Predictive maintenance, diagnostics and battery management
FPGAs facilitate localized AI processing, allowing continuous monitoring of sensors, electrical and mechanical systems within the vehicle to predict potential failures before they occur and alert the vehicle owner of the need for preventative maintenance or repairs. They can also do localized monitoring of battery state-of-health and state-of-charge to perform advanced management and load balancing of battery cells to extend battery life and reduce the need for battery maintenance or replacement. AI capability within the FPGA is essential for time-sensitive sensing and diagnoses where fast, accurate insights can lead to increased reliability and extended life of the vehicle and its battery.
Automotive Applications
Advanced Driver-Assistance System (ADAS)
ADAS applications enhance vehicle safety and driving convenience by integrating cutting-edge sensors, real-time data processing, and automation to assist drivers in making more informed decisions and reducing the risk of accidents. FPGAs enable ADAS by providing the required computational power, real-time performance, flexibility, and energy efficiency, making them a crucial component in the development of next-generation automotive systems.
Software-Defined Vehicle (SDV)
The transformation to an SDV relies on software to control, manage, and enhance nearly every aspect of the vehicle’s operation, enabling continuous improvement and adaption to new technologies and user demands. FPGAs are critical to this new architecture, providing the reconfigurability, high-speed processing, energy efficiency, and security needed to support a constantly evolving, software-centric automotive platform.
Electric Vehicle (EV) Powertrain
Pioneering the next generation of mobility, the EV powertrain integrates advanced technologies to efficiently convert and manage electrical energy, delivering optimal performance, range, and sustainability while enabling precise control of motor operation and power distribution. FPGAs provide real-time control, power management, reconfigurability, safety, and AI integration, leading to more efficient, reliable, and adaptable systems for the future of EVs.
Fast DC Charger
As transportation vehicles are electrified, attention switches from fuel consumption to electrical energy consumption and the efficiency and cost of power converters. DC Fast Charging (DCFC) technology is used in level 3 EV charging stations where the charging happens fully within the station, and it uses DC power, allowing users to charge an EV in as little as 30 minutes fully.
FPGAs are unique in enabling custom digital control at very high frequencies. They are beneficial in reducing the size and cost of passive components and minimizing the power lost in AC/DC power conversion.
FPGAs also support battery management. Unlike charging with AC power, DC fast charging risks overloading EV batteries, which could contribute to their decay or loss of range over time. FPGAs support batteries and BMS by providing the compute necessary to evenly distribute loads across cells, eliminating the threat of decay and providing greater longevity to the battery.
Read the Electric Vehicle (EV) Charging eBook ›
Watch the video on EV charging solutions from Intel and Imagen Energy ›
See the Three-Phase Boost Bi-directional AC/DC Converter design example ›
Browse Products To Get Started
Our automotive-grade devices feature junction temperature support from -40°C to +125°C (or higher on selected devices). These devices meet or exceed ISO 9001:2001, AEC-Q100 standards, and ISO 26262. All our automotive-grade devices are manufactured at fully IATF-16949-registered/certified sites using some of the programmable logic industry’s smallest, highest-reliability, and mainstream semiconductor fabrication processes. Our automotive-grade portfolio spans CPLDs to FPGAs and also includes SoCs and power management PowerSoCs.
Cyclone® V FPGAs
Cyclone® V SoC FPGAs
MAX® 10 FPGAs
MAX® V FPGAs
Development Kits
FAQs
Frequently Asked Questions
A “Software Defined Vehicle” or SDV is defined as a vehicle that uses software to manage its operations, add functionality, and enable new features through software. Altera FPGAs and SoCs are ideally suited for software defined vehicles because they can execute many different tasks concurrently with the efficiency and deterministic performance of hardware, but they can be updated over time so that carmakers can add functionality and enable new features without sacrificing performance or efficiency. In other words, Altera FPGAs offer hardware-like performance and determinism along with software-like flexibility and programmability.
There are many ways in which the AI capabilities of Altera FPGAs and SoCs can be used to make vehicles smarter, safer, more efficient, reliable, enjoyable and easier to operate. In order to make vehicles safer and easier to operate, the automotive industry is seeing a dramatic proliferation of cameras and other types of sensors, such as LiDAR, RADAR and motion sensors around the vehicle and within the cockpit. Altera FPGAs and SoCs have specialized, AI-enabled Digital Signal Processors (DSPs), embedded throughout their logic fabric, which can be used to perform the demanding matrix multiplication tasks that AI requires. These AI-enabled DSPs allow for very fast and efficient processing and fusion of sensor data so that it can processed efficiently, making the vehicle smarter and safer. The AI capabilities of Altera FPGAs and SoCs can also be used by Driver and Occupant Monitoring Systems (DMS and OMS) within the vehicle to monitor driving behavior and keep drivers and occupants safer and more comfortable. In addition, AI can be used for voice recognition to allow drivers and passengers to safely and easily interact with the vehicle and AI can be used to monitor electrical and mechanical systems of the vehicle and predict the need for maintenance or repairs.
Altera offers numerous devices, from small, efficient CPLDs to high-performance FPGAs and SoCs which are suitable for Automotive use. All of Intel's automotive-grade devices are AEC-Q100 certified and qualified to operate at -40°C to +105°C ambient temperature (Auto Grade 2). This range addresses the majority of infotainment and ADAS applications where vehicles must operate in a wide range of temperature conditions. In addition, many of these devices are ASIL-certified according to ISO 26262.
Yes, Altera offers both devices and tools which are ASIL-certified according to ISO 26262 and Altera follows an ASIL-compliant development process which allows the devices to be used in safety-critical automotive systems. In addition, Altera offers ASIL-certified development tools and an Automotive Functional Safety Data Package (AFSDP) to facilitate the design of Altera products into safety-critical systems.
The Automotive-Grade Device Handbook (PDF) contains a list of all available Automotive Grade Devices. Further details can be found in the data sheet or handbook for each device
family.