Electric Propulsion Peak Power Control With a State Machine
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Solution Overview
Problem
Existing electric propulsion systems face challenges in operating above continuous rated conditions due to component degradation, with complex programming and difficult diagnostics, making it hard to manage peak power effectively.
Innovation Solution
A state machine is implemented to control maximum power output, allowing the system to operate in multiple states, including exceeding or constraining power, and is designed to manage power efficiently, with transitions based on operating conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the electric propulsion system operates above continuous rated conditions to increase vehicle drivability and performance, then vehicle drivability and performance are improved, but component degradation occurs
Solution Approach 1:
The system dynamically adjusts power output based on real-time monitoring of component temperatures and operating conditions. The controller continuously evaluates whether components are approaching degradation thresholds and adjusts the maximum allowable power accordingly, allowing peak operation when safe and reducing power when components are at risk, thus resolving the contradiction between performance and reliability
Solution Approach 2:
The system implements a feedback mechanism where sensors monitor component temperatures and operating conditions, and this information is fed back to the controller which adjusts power output limits. This closed-loop control allows the system to operate at peak performance when conditions permit while automatically preventing degradation when components approach critical thresholds
2Reliability
If hardware or software monitors are added to enforce electric propulsion system operating constraints, then component degradation is prevented, but programming complexity increases
Solution Approach 1:
The control system is segmented into discrete, well-defined states (e.g., normal operation, peak power, cooling, shutdown) with clear transition criteria between them. This state-machine approach breaks down the complex monitoring and control logic into manageable, independently testable segments, reducing programming complexity while maintaining reliable constraint enforcement
Solution Approach 2:
The system uses clearly defined parameter thresholds (temperature limits, power levels, time durations) to trigger state transitions. By basing control logic on explicit parameter changes rather than complex conditional reasoning, the programming becomes more straightforward and easier to verify, while still effectively preventing component degradation
3Measurement precision
If multiple input conditions and conditional statements are included to manage peak power, then power control accuracy is improved, but system diagnostics become difficult and time-consuming
Solution Approach 1:
The system transitions between discrete, well-defined states based on monitored parameters, with each state having explicit entry and exit criteria. This dynamic state-machine structure provides a clear diagnostic path: technicians can determine system status by identifying the current state and comparing it against expected state transitions, making diagnostics straightforward despite multiple input conditions
Solution Approach 2:
The state machine acts as an intermediary layer between the complex sensor inputs and the power control outputs. Rather than directly processing numerous conditional statements, the system uses states as intermediate representations of system condition, simplifying diagnostics by providing a clear mapping between observed behavior and underlying causes
Data Source
AI summary
Methods and systems for controlling a maximum power output of an electric propulsion system are described. In one example, a state machine generated from executable instructions controls a maximum power output of an electric propulsion systems. The state machine permits additions states and changes to conditions that facilitate transitioning between the various states without having to completely reconstruct the maximum power output method.