Functional Safety Insights For Today’s Automotive Industry

As cars have evolved into rolling computing platforms, vehicle safety now extends well beyond the traditional seat belt. While they still take us to the grocery store, they also integrate advanced technology, enabling the rapid fusion of multimodal data through edge devices such as sensors and actuators.

Modern vehicles offer unprecedented safety, but they can contain between one to three thousand chips, where even a single sensor malfunction can result in a hazardous situation.

Let’s discuss five essential insights into automotive functional safety.

Safety starts with industry cooperation

Achieving uniform safety in the automotive industry requires collaboration under a common framework. By adhering to these technology-agnostic standards, manufacturers can build safer vehicles and reduce costs associated with redesigns and recalls due to safety issues. This is why the International Organization for Standardization (ISO) works with auto manufacturers (OEMs) and their suppliers to develop standards like ISO 26262, which governs the functional safety of electrical and electronic systems in road vehicles.

One component of ISO 26262 is the Automotive Safety Integrity Level (ASIL) classification, ranging from ASIL-A to ASIL-D, with ASIL-D demanding the most rigorous safety measures. ASIL-D serves as a critical benchmark for assessing and ensuring the reliability and safety of systems-on-chip (SoCs) and 3D integrated circuits (ICs) in applications where failure could have severe consequences.

To create SoCs that meet these stringent safety requirements, system architects collaborate with engineers to incorporate automotive-grade IP alongside ISO 26262-certified, safety-aware testing and design implementation.

Furthermore, my committee at the Institute of Electrical and Electronics Engineers (IEEE) oversees IEEE P2851, which provides guidelines for designing, implementing, and evaluating safety-critical systems. This standard outlines essential methods, description languages, data models, and databases that can be utilized across the industry.

Standards are essential because, as we incorporate more technology, we also introduce more risk. These standards, along with others that govern vehicle safety, facilitate the exchange and interoperability of data throughout the vehicle’s lifecycle. They also adapt as new technologies such as AI emerge.

The balance of risk and reward

Integrating AI components into modern vehicles offers numerous advantages, such as park assist and real-time road situation analysis. However, it also comes with certain trade-offs.

High-performance systems-on-chip (SoCs) that handle AI workloads consume more power, affecting energy efficiency, especially in electric vehicles. Additionally, 3D integrated circuits (ICs) pose thermal management challenges, requiring effective cooling solutions to ensure reliability and longevity. This is particularly crucial for electric vehicles, where battery life and thermal stability are major concerns.

The addition of extra chips and safety features increases complexity, raising the risk of failure. Data security is another significant concern, along with the material costs of new technologies, which can impact profit margins and affordability.

As a result, functional safety becomes a balancing act for OEMs, who must consider safety mechanisms alongside budget constraints, performance requirements, and security needs.

There is no safety if technology is not secure

To ensure tamper-proof data transfer among the many sensors and components in modern vehicles, it is essential to adopt a comprehensive security approach.

First, in-vehicle networks must incorporate the security expertise gained over the past 30 years in the networking world. This means integrating security into the system architecture in the earliest stages of design rather than making it an afterthought. Encryption for data in transit and at rest, multi-factor authentication, secure communication protocols, and regular security audits are all recommended.

Second, hardware-based security features such as secure enclaves, trusted execution environments (TEEs), and intrusion detection and prevention systems (IDPS) play a vital role in defending against threats. These features protect sensitive data and system integrity. Additionally, using hardware security modules (HSMs) and secure boot processes ensures only authenticated and untampered firmware and software can operate within the vehicle’s electronic control units (ECUs).

Finally, adhering to the ISO 21434 standard is vital for comprehensive vehicle security. This standard covers the entire vehicle lifecycle, emphasizing risk management, organizational and technical requirements, and continuous monitoring.

Data and transmission security help prevent tampering and ensure predictable vehicle operation — but components that govern security also use chips. We must practice predictive maintenance to ensure those chips are operating safely.

Predictive maintenance boosts vehicle reliability

Predictive maintenance utilizes advanced analytics and machine learning algorithms to forecast potential failures before they happen. This approach can be applied to any vehicle component and is increasingly used at the silicon level to anticipate chip degradation.

Predictive maintenance techniques can monitor the health of critical systems like the engine’s electronic control unit (ECU) or the battery management system (BMS) in electric vehicles. By predicting when key components might fail, these techniques enable timely maintenance.

To achieve optimal results, the vehicle’s operating system must analyze vast amounts of data using advanced technologies capable of identifying patterns and predicting potential failures with high precision. This involves leveraging edge computing to process data locally on the vehicle and cloud computing to aggregate and analyze data at scale.

Advanced machine learning models are trained on both historical and real-time data to recognize early signs of component degradation. For instance, a machine learning algorithm might detect a subtle increase in operating temperature that indicates an impending chip failure, allowing maintenance to be scheduled before any damage occurs.

However, to fully harness the benefits of predictive maintenance, a comprehensive framework for managing and effectively utilizing this vast amount of data is essential. This is where Silicon Lifecycle Management (SLM) plays a crucial role.

Silicon Lifecycle Management is intrinsic to automotive functional safety

SLM offers a comprehensive approach to managing the data and processes associated with the maintenance and service of vehicle components throughout their lifecycle. By integrating SLM with predictive maintenance, cybersecurity, and industry standards, manufacturers can ensure that maintenance activities are timely and aligned with the overall vehicle service strategy.

Synopsys provides a broad portfolio of standards-based, automotive-grade IP, including interface, processor, security, and foundation IP. These components are compliant with industry standards, helping accelerate SoC-level design and qualification.

Synopsys also offers a comprehensive set of integrated, standards-based Silicon Lifecycle Management (SLM) tools, IP, and methodologies that provide observability, analytics, and automation at the silicon level. Our Process, Voltage, and Temperature (PVT) Monitor IP, for example, is certified as ASIL-B ready and meets the AEC-Q100 Grade 2 standard.

Gathering data at every phase of the product lifecycle, Synopsys SLM solutions provide continuous analysis and actionable insights. Not only does this improve design efficiency and quality, but it also helps predict in-field chip degradation or failure.

Ensuring vehicle safety with a silicon-to-systems strategy

Human error is responsible for the vast majority of automotive accidents. Modern cars, equipped with numerous sensors and safety features, can help mitigate these errors by alerting drivers to hazardous conditions or even taking corrective actions. However, these same sensors and safety features also add complexity and potential risks.

To ensure functional safety, it is crucial to continue promoting and enhancing essential industry standards. We must ensure the security of data flowing into, out of, and within each vehicle. Additionally, we need to leverage solutions that offer end-to-end monitoring, verification, and predictability – from silicon to systems.