Adaptive Speed Profile Control for Hybrid Vehicles
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Solution Overview
Problem
Current engine control strategies for electrified and plug-in hybrid vehicles optimize fuel consumption based on synthetically modulated speed profiles without considering actual traffic conditions, leading to suboptimal energy usage.
Innovation Solution
A method that adapts the synthetically modulated speed profile to the actual traffic situation by selecting routes, dividing them into segments, recording stopping processes, and adjusting speed curves based on detected stopping events, using a maneuver class matrix with constant, acceleration, and deceleration classes to optimize energy efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If a synthetically modulated speed profile is used for engine control optimization, then energy consumption is reduced, but the control strategy cannot be optimally adapted to actual traffic conditions
Solution Approach 1:
The system records actual stopping processes during vehicle operation and uses this feedback to adapt the synthetically modulated speed profile. The control device compares predicted stopping events with actual stopping events and adjusts the speed profile parameters accordingly, enabling the system to learn from real traffic conditions while maintaining the energy optimization benefits of synthetic profiling
Solution Approach 2:
The speed profile is transformed from a static synthetic model to a dynamic adaptive system that evolves based on recorded traffic patterns. The system continuously updates the speed profile by incorporating actual stopping process data, allowing it to adapt to changing traffic conditions while preserving the energy efficiency advantages of structured profile-based control
2Use of energy by moving object
If the route is divided into segments with assigned maneuver classes for speed profile generation, then energy efficiency is improved, but the system complexity increases
Solution Approach 1:
The route is divided into discrete segments with assigned maneuver classes (constant-speed, acceleration, deceleration), creating a structured framework for speed profile generation. This segmentation enables energy-efficient control by optimizing each segment independently while maintaining overall route optimization, and the modular structure manages complexity through systematic classification
3Adaptability or versatility
If stopping processes are recorded and used to adapt speed profiles in real-time, then adaptability to traffic conditions is improved, but the data processing requirements and system complexity increase
Solution Approach 1:
The system extracts only the essential characteristics of stopping processes (frequency, duration, location) from raw sensor data, rather than processing complete traffic data streams. This extraction approach enables effective adaptation to traffic conditions by focusing on the most relevant parameters for speed profile adjustment while minimizing data processing complexity and computational requirements
Data Source
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AI summary
The present invention relates to a method for traffic-flow-conditioned adaptation of stopping processes to a synthetically modulated speed profile along a route travelled along by a vehicle, having the steps a) selecting a route on the basis of map data stored in a data record S1, b) dividing the route into route segments and generating a synthetically modulated speed profile for each route segment S2, c) travelling along at least part of the route by a driver with the vehicle S3, d) sensing how often and how long the vehicle stops in the route segments travelled through as it travels along at least part of the selected route 54, and e) adaptation of at least one synthetically modulated speed profile for at least one route segment to the detected stopping processes S5. The present invention also relates to a control device for carrying out the method according to the invention.