HEV Torque Allocation via Route Segmentation
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Solution Overview
Problem
Hybrid Electric Vehicle (HEV) control systems face challenges in minimizing energy operational costs and emissions while maintaining vehicle drivability, particularly in optimizing fuel consumption and battery state of charge across varying driving conditions without compromising computational efficiency.
Innovation Solution
A controller is programmed to forecast torque allocation between the engine and electric machine for predetermined route segments, adjusting engine activation based on predicted driver demand and battery state of charge to achieve target battery state at each segment endpoint, utilizing path forecasting and segmentation to optimize energy management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the controller optimizes energy management by forecasting torque allocation and adjusting engine activation across route segments, then fuel efficiency and emissions are improved, but computational complexity and real-time processing requirements increase
Solution Approach 1:
The route is divided into multiple predetermined route segments with endpoints, allowing the controller to optimize energy management for each segment independently. This segmentation enables forecasted torque allocation and engine activation adjustments to be calculated for smaller, manageable portions of the overall journey, reducing the computational burden while maintaining fuel efficiency improvements.
Solution Approach 2:
The controller forecasts torque allocation and determines optimal engine activation points in advance for each route segment before actual traversal. By performing these calculations preliminarily for each segment, the system can optimize fuel consumption without requiring complex real-time computations during vehicle operation.
2Measurement precision
If the controller monitors and adjusts battery state of charge at each route segment endpoint, then energy management precision is improved, but measurement and control requirements increase
Solution Approach 1:
The route is segmented into multiple sections with defined endpoints, and the controller monitors battery state of charge specifically at these segment endpoints rather than continuously throughout the entire route. This segmented monitoring approach achieves precise battery state control while reducing the overall complexity of the measurement and control system compared to continuous monitoring.
Solution Approach 2:
The controller applies localized control by monitoring and adjusting battery state of charge at specific locations (segment endpoints) rather than uniformly across the entire route. This local quality approach allows precise energy management at critical points while simplifying the control system in between these points.
3Use of energy by moving object
If the controller forecasts torque allocation based on predicted driver demand, then energy operational costs are reduced, but prediction accuracy requirements and computational load increase
Solution Approach 1:
The controller forecasts torque allocation separately for each predetermined route segment rather than for the entire route as a single unit. This segmentation of the prediction task reduces the computational load and complexity of the prediction model while still achieving reduced energy operational costs through optimized torque distribution across all segments.
Data Source
AI summary
A vehicle includes a powertrain having an engine and an electric machine, and a battery configured to power the electric machine. The vehicle further includes a controller programmed to operate the powertrain according to a forecasted torque allocation between the engine and the electric machine. The controller generates forecasted torque allocation for each of a plurality of predetermined route segments based on predicted driver demand. The forecasted torque allocation is confirmed for each of the route segments based on a target battery state of charge corresponding to an endpoint of the route segment while an actual state of charge is within a threshold value of the target battery state of charge.