Leveraging Existing DFT/Architecture for Latent Fault Coverage

Abstract

The increasing complexity of automotive electronic systems necessitates robust diagnostic strategies to detect and mitigate latent faults effectively. Design-for-Test (DFT) methodologies, originally developed for manufacturing test, can be leveraged to enhance in-field diagnostics. This white paper explores strategies to utilize existing DFT and system architecture for latent fault detection, including test time optimizations through key-on/key-off strategies and real-time, on-the-go diagnostics.

Introduction

ISO 26262 mandates the detection and handling of latent faults to ensure functional safety in automotive systems. Traditional Built-In Self-Test (BIST) and other DFT methodologies primarily focus on production testing but can be extended to address in-field diagnostics. This paper outlines methodologies for leveraging existing DFT/architecture for safety-critical applications.

Challenges in Latent Fault Coverage

Limited In-Field Testing Capabilities: Traditional production test structures are not optimized for in-field applications.
Test Time Constraints: Testing during key-on and key-off phases must balance thorough coverage with startup time limitations.
Resource Utilization: Reusing DFT structures without impacting normal operation requires architectural considerations.
On-the-Go Diagnostics: Implementing runtime monitoring without excessive performance overhead.

Strategies for Latent Fault Detection

1. Reusing DFT for In-Field Tests

Utilize existing scan chains for periodic in-field testing.
Leverage BIST mechanisms for periodic self-checks.
Enable memory BIST (MBIST) execution during non-critical operations.

2. Optimizing Test Time Using Key-On/Key-Off Strategies

Execute quick, high-priority tests during the key-on phase.
Perform extended self-tests during the key-off phase.
Utilize predictive analytics to prioritize test execution based on failure history.

3. On-the-Go Diagnostics for Continuous Monitoring

Integrate built-in error detection mechanisms within processing pipelines.
Utilize software-based test pattern execution during idle cycles.
Leverage hardware performance monitors for anomaly detection.

4. Adaptive Test Scheduling and Fault Injection

Implement dynamic test scheduling based on operating conditions.
Use fault injection mechanisms to validate diagnostic coverage.
Adapt test strategies based on real-time system performance.

Implementation Considerations

DFT-Aware System Architecture: Ensure design supports test execution without impacting functional performance.
Efficient Power Management: Minimize energy consumption during test phases.
Scalability: Ensure methodologies adapt to increasing system complexity.
Compliance with Safety Standards: Validate strategies against ISO 26262 requirements.

Conclusion

By leveraging existing DFT methodologies, automotive systems can achieve improved latent fault coverage while optimizing test execution times. Implementing key-on/key-off strategies, on-the-go diagnostics, and adaptive test scheduling enhances safety and reliability without significant hardware modifications. Future advancements in AI-driven diagnostics and predictive maintenance will further refine these approaches.

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