e-AWD and e-LSD Supervisory Torque Control for Vehicle Stability
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Solution Overview
Problem
Current motor vehicle control systems face challenges in maintaining vehicle stability and optimizing tire force generation in complex driving scenarios, particularly in situations involving tire slip, while also requiring reduced cost, complexity, and calibration efforts, and increased redundancy and robustness.
Innovation Solution
A supervisory control system for eAWD and eLSD in motor vehicles, utilizing sensors and actuators to monitor and adjust wheel and axle torques based on real-time data, including inertial measurements, wheel speeds, and tire pressures, to actively manage torque transfer and maintain stability by adjusting control signals within actuator boundaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex control systems with multiple sensors and actuators are used to manage vehicle stability and tire slip, then vehicle control precision and stability are improved, but device complexity and calibration requirements increase
Solution Approach 1:
The control system is segmented into modular functional components: a supervisory controller that manages overall coordination, individual sensor modules (inertial measurement units, wheel speed sensors, throttle position sensors), and actuator modules. Each component operates semi-independently with defined interfaces, allowing the complex system to be divided into manageable segments that can be calibrated and maintained separately, thus reducing overall system complexity while maintaining stability.
Solution Approach 2:
The supervisory controller acts as an intermediary between the various sensors and actuators in the system. It receives data from multiple sensor sources, processes this information, and generates coordinated control signals to the actuators. This intermediary layer simplifies the control architecture by centralizing the coordination logic, reducing the need for complex direct connections between all sensors and actuators, and thereby reducing device complexity while ensuring reliable vehicle stability control.
2Measurement precision
If multiple sensors and actuators are integrated to provide comprehensive vehicle data and control, then measurement precision and control accuracy are improved, but device complexity and cost increase
Solution Approach 1:
The supervisory controller is designed as a multi-functional device that performs several critical functions: it coordinates torque transfer between axles, monitors vehicle stability, processes sensor data from multiple sources, and generates actuator control signals. This universal controller consolidates what would otherwise require multiple specialized control units, thereby maintaining high measurement precision and control accuracy while reducing the number of separate components and simplifying the overall integration architecture.
Solution Approach 2:
Multiple sensor functions and actuator control functions are merged into a unified supervisory control system. The system combines inertial measurement data, wheel speed data, and throttle position data into a single coordinated control decision-making process. This merging approach maintains comprehensive measurement precision by integrating multiple data sources while reducing device complexity by eliminating the need for separate dedicated control systems for each function.
3Productivity
If advanced control algorithms are implemented to optimize torque distribution and maintain stability, then vehicle performance and driver control are improved, but computational requirements and processing time increase
Solution Approach 1:
The supervisory controller is pre-programmed with control algorithms and decision-making logic that enable it to rapidly process sensor data and generate appropriate control signals. By having the control strategy pre-established in the controller's memory and processing unit, the system avoids the need for complex real-time calculations during critical moments, thereby maintaining optimized torque distribution while minimizing processing time delays. The controller is prepared in advance with the computational framework needed to respond quickly to changing vehicle conditions.
Data Source
AI summary
A system for supervisory control for eAWD and eLSD in a motor vehicle includes a control module, and sensors and actuators disposed on the motor vehicle. The sensors measure real-time motor vehicle data, and the actuators alter behavior of the motor vehicle. The control module receives the real-time data; receives one or more driver inputs to the motor vehicle; determines a status of a body of the motor vehicle; determines a status of axles of the motor vehicle; determines a status of each wheel of the motor vehicle; and generates a control signal to the actuators from the driver inputs and the body, axle, and wheel statuses. The control module also exercises supervisory control by actively adjusting constraints on the control signal to each of the actuators where actively adjusting constraints on the control signal alters boundaries of control actions in response to the one or more driver inputs.