Vehicle Door Obstruction Detection Using Condition-Based Motor Current
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Solution Overview
Problem
Existing vehicle door control systems do not account for changing vehicle conditions, such as pitch and roll, which can lead to injuries or damages due to inadequate force management during door operation.
Innovation Solution
The system determines the expected current required to operate a vehicle door based on conditions like pitch, roll, temperature, and voltage, using sensors and look-up tables, and compares it to the actual current to detect obstructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing door control systems operate doors using fixed force without accounting for vehicle conditions, then the system is simple and reliable, but it cannot detect obstructions accurately under varying conditions leading to safety hazards
Solution Approach 1:
The system continuously monitors actual current consumption during door operation and compares it against expected current values that account for vehicle conditions (pitch, roll, temperature, voltage). This feedback mechanism enables accurate obstruction detection by identifying deviations between expected and actual current, thereby improving safety without requiring overly complex hardware additions.
Solution Approach 2:
The system dynamically adjusts the expected current threshold based on changing vehicle parameters such as pitch angle, roll angle, temperature, and voltage levels. By adapting the obstruction detection threshold to these varying conditions, the system maintains high reliability across different operating scenarios without requiring a completely complex system redesign.
2Measurement precision
If the system accounts for changing vehicle conditions like pitch and roll, then obstruction detection accuracy improves, but the device complexity increases
Solution Approach 1:
The control system implements a feedback loop that continuously compares actual current consumption with expected current values calculated based on vehicle conditions. This feedback mechanism enables precise obstruction detection by identifying current deviations that indicate obstructions, while using software-based calculations rather than additional complex hardware sensors.
Solution Approach 2:
The system replaces complex mechanical obstruction detection mechanisms with an electrical current-based detection method. By monitoring current consumption patterns and comparing them against condition-adjusted expectations, the system achieves high measurement precision using electrical measurements rather than mechanical sensors or complex mechanical feedback systems.
3Productivity
If the door operates without considering vehicle pitch and roll, then the operation is fast and simple, but it may cause injuries or damages due to inadequate force management
Solution Approach 1:
The system performs preliminary calculations of the expected current required for door operation based on vehicle conditions (pitch, roll, temperature, voltage) before actually operating the door motor. This advance preparation allows the control system to have the correct force thresholds ready, enabling fast door operation while maintaining safety through pre-computed condition-appropriate force levels.
Solution Approach 2:
The system dynamically adjusts door operation parameters based on real-time vehicle conditions. By continuously monitoring pitch, roll, temperature, and voltage, the system adapts the expected current thresholds to match current operating conditions, allowing fast operation when conditions are favorable while preventing injuries or damages when conditions require more cautious force management.
Data Source
AI summary
Techniques for controlling a vehicle based on a collision avoidance algorithm are discussed herein. The vehicle receives sensor data and can determine that the sensor data represents an object in an environment through which the vehicle is travelling. A computing device associated with the vehicle determines a collision probability between the vehicle and the object at predicted locations of the vehicle and object at a first time. Updated locations of the vehicle and object can be determined, and a second collision probability can be determined. The vehicle is controlled based at least in part on the collision probabilities.