Vehicle Telemetry Predictive Control for Powertrain Temperature
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Solution Overview
Problem
Existing route look-ahead systems for vehicles do not account for dynamic characteristics and vehicle subsystem dynamics, leading to suboptimal vehicle operating parameter adjustments.
Innovation Solution
A remote server receives operating parameters from a vehicle controller, combines them with static and dynamic information such as road and weather data, and sends commands to adjust vehicle components for optimal operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If traditional route look-ahead systems are used to identify static characteristics ahead of the vehicle, then fuel efficiency can be improved, but the system does not account for dynamic characteristics and vehicle subsystem dynamics, leading to suboptimal adjustments
Solution Approach 1:
The system transitions from static route characteristics to dynamic characteristics by incorporating real-time weather data, traffic conditions, and vehicle subsystem states. The predictive control model continuously updates predictions based on changing conditions, enabling adaptive optimization of vehicle operating parameters throughout the journey.
Solution Approach 2:
The system performs preliminary predictions of future vehicle states and optimal control actions by integrating current operating parameters with forecasted dynamic conditions. This allows the system to proactively adjust vehicle parameters before suboptimal conditions occur, rather than reacting after deviations happen.
2Use of energy by moving object
If traditional route look-ahead systems adjust vehicle operating parameters, then some fuel efficiency benefits are achieved, but vehicle subsystem dynamics and operating constraints are not taken into account
Solution Approach 1:
The system implements a closed-loop predictive control framework where actual vehicle subsystem responses are continuously monitored and fed back into the prediction model. This feedback mechanism allows the system to learn from real subsystem behavior, refine predictions, and adjust control strategies to account for actual subsystem dynamics and constraints.
Solution Approach 2:
The system dynamically adjusts multiple vehicle operating parameters simultaneously based on predicted optimal trajectories, considering subsystem-specific constraints and dynamics. Each subsystem's operating parameters are optimized within its operational boundaries while coordinating with other subsystems for overall vehicle efficiency.
3Productivity
If more comprehensive information is integrated for vehicle control, then optimization of vehicle operating parameters improves, but system complexity increases
Solution Approach 1:
The system segments the complex vehicle control problem into multiple predictive models, each dedicated to specific vehicle subsystems. This modular approach allows independent development and optimization of subsystem models while maintaining overall system coordination through the integrated predictive control framework.
Solution Approach 2:
The predictive control model serves as an intermediary layer that processes comprehensive vehicle and environmental data, then translates complex information into coordinated control commands for various subsystems. This intermediary structure simplifies the control architecture by centralizing the decision-making logic while maintaining subsystem independence.
Data Source
AI summary
A control system for a vehicle includes one or more processing circuits. The one or more processing circuits have programmed instructions to acquire a temperature of a component of the vehicle, acquire at least one of static information or dynamic information regarding one or more route characteristics ahead of the vehicle, determine an adjustment to one or more powertrain components of the vehicle based on (a) the temperature and (b) the at least one of the static information or the dynamic information indicating that an upcoming event is expected to cause the temperature of the component to operate outside of a target temperature range, and implement the adjustment to the one or more powertrain components of the vehicle to preemptively adjust the temperature of the component of the vehicle in advance of the upcoming event to maintain the temperature within the target temperature range as the upcoming event is traversed.