Vehicle Steering Control Redundancy via Cross-Verification
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Solution Overview
Problem
In autonomous driving systems, a steering system must continue to function safely even after an error occurs, without relying on the driver, and existing solutions require redundant design but struggle to accurately identify errors without unnecessary power reductions or shutdowns, particularly in monitoring rotor position sensors.
Innovation Solution
A method using two microcontrollers with decision-maker modules to compare sensor data and calculate ideal and real rotor behavior, allowing a majority decision to suppress faulty sensor control, eliminating the need for a third sensor and ensuring safety through software-based redundancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dual-redundant design is implemented with two control circuits, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent merges the monitoring function into the existing dual-redundant control structure by having each microcontroller monitor both its own sensor and the other microcontroller's sensor. This eliminates the need for separate monitoring circuits while maintaining reliability through cross-verification of sensor data between the two redundant control paths.
2Measurement precision
If a third sensor is added for fault verification, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
Instead of adding a third physical sensor, the patent creates a virtual copy of the sensor monitoring function through software. Each microcontroller generates expected sensor values based on its control commands and compares these calculated values with actual sensor readings from both sensors. This software-based copying approach achieves fault detection capability without additional hardware sensors.
Solution Approach 2:
The patent replaces the mechanical/sensor-based fault detection approach with a software-based calculation and comparison system. Rather than using additional physical sensors to detect faults, the system uses microcontrollers to calculate expected sensor values and compare them with actual readings, substituting computational logic for physical sensing infrastructure.
3Reliability
If fault detection is made more sensitive, then reliability is improved, but false fault detection increases leading to unnecessary power reductions
Solution Approach 1:
The patent implements a feedback mechanism where each microcontroller continuously compares actual sensor readings with calculated expected values and uses this feedback to determine whether a genuine fault exists. The comparison between actual and calculated values provides feedback that filters out noise and transient errors, enabling reliable fault detection while avoiding false positives that would trigger unnecessary power reductions.
Data Source
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AI summary
The invention relies on a special hardware architecture for controlling a safety-relevant process. At least two microcontrollers (250, 350) are used to control the process in at least two control circuits, with each microcontroller (250, 350) being specifically configured to control the safety-relevant process. This is therefore a redundant system. In this method, the microcontrollers (250, 350) process the data from at least one sensor (276, 376) that detects the actual behavior of the respective control circuit. The data from the respective sensor (276, 376) is exchanged between the two microcontrollers (250, 350), and a decision module (258, 358) provided for each microcontroller (250, 350) checks whether the sensor data (276, 376) is consistent.Upon detection of an inconsistency, a majority decision is formed. In this process, the microcontroller (250, 350) calculates a model value based on control commands. This model value is then used to determine whether the microcontroller (250, 350) of the control train whose data was identified as faulty in the majority decision is controlling the safety-relevant process. Calculating this model value eliminates the need for a third sensor that would otherwise be required for verification.