Multi-Unit Vehicle Control Allocation for Distributed Propulsion
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Solution Overview
Problem
Conventional control systems for multi-unit vehicle combinations, particularly those with distributed propulsion and energy storage, often fail to account for global factors, leading to underdetermined control issues due to over-actuation, as they are typically tailored to specific configurations and address the problem on a unit level.
Innovation Solution
A system and method that determine a virtual control input for the vehicle combination based on global factors, including power management and target motion parameters, using a target generator, power manager, and combination control allocator to adapt control allocation to different configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional control allocation methods are used for multi-unit vehicle combinations, then each unit is controlled independently, but the system lacks coordinated control capability and cannot optimize overall vehicle performance
Solution Approach 1:
The control system is segmented into multiple control units, each responsible for a specific vehicle unit (e.g., tractor, trailer, semitrailer). Each control unit independently calculates control allocations for its associated actuator, enabling distributed coordinated control while maintaining system modularity and avoiding centralized complexity.
Solution Approach 2:
The patent introduces a hierarchical control architecture that adds a temporal dimension to control allocation. The dynamic control allocation considers future control demands and current actuator states across multiple time steps, transforming the control problem from static to dynamic optimization across the time dimension.
2Productivity
If dynamic control allocation considering actuator states and future demands is implemented, then control optimization is improved, but computational complexity and processing time increase
Solution Approach 1:
The control system performs preliminary calculations by predicting future control demands and actuator states ahead of time. The dynamic control allocation algorithm pre-computes optimal control allocations considering anticipated vehicle dynamics and actuator constraints, reducing real-time computational burden while maintaining optimization quality.
Solution Approach 2:
The patent implements a dynamic control allocation framework that continuously adapts control allocations based on real-time actuator states and predicted future demands. The system dynamically adjusts control signals across multiple time steps, optimizing performance while respecting actuator constraints through time-varying control strategies.
3Adaptability or versatility
If centralized control allocation is used for all vehicle units, then coordinated control is achieved, but system reliability decreases due to single point of failure
Solution Approach 1:
The control architecture is segmented into multiple independent control units, each managing its associated vehicle unit. This distributed segmentation eliminates single points of failure, as each control unit can operate independently if others fail, while still achieving coordinated control through inter-unit communication and shared optimization objectives.
Solution Approach 2:
The patent introduces an intermediary optimization layer that coordinates between distributed control units. This intermediary layer facilitates information exchange and cooperative optimization without creating a centralized control point, allowing control units to achieve coordinated performance while maintaining independence and reliability.
Data Source
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AI summary
A computer-implemented method (400) for controlling a vehicle combination (100) comprising a tractor unit and at least one trailing unit is disclosed. The method comprises: determining (406) a power allocation input for the vehicle combination based on a reference input for the vehicle combination and a power capability of one or more units (110) of the vehicle combination; determining (410) a virtual control input for the vehicle combination based on the reference input; and determining (412, 414, 416) a control input for the vehicle combination based on the power allocation input and the virtual control input. A corresponding computer program product, control system, non-transitory computer-readable storage medium, computer system and vehicle are also disclosed.