Adaptive EV Eco Cruise Control for Drive Unit Efficiency
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Solution Overview
Problem
Current cruise control systems for electric vehicles do not optimize efficiency, leading to suboptimal vehicle efficiency and range, as they operate at a fixed velocity without considering factors like road grade, vehicle mass, and traction force, which can be improved by implementing an adaptive eco-cruise strategy.
Innovation Solution
A computer-implemented method that determines an eco-cruise control velocity based on vehicle dynamic information, such as road grade and traction torque, to maximize drive unit efficiency by selecting from a range of candidate velocities within a specified tolerance, adjusting the velocity in real-time to maintain optimal efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional cruise control operates at a fixed velocity set point, then the vehicle maintains a constant speed, but the vehicle efficiency is not optimized
Solution Approach 1:
The cruise control system transitions from a static fixed velocity operation to a dynamic adaptive velocity selection. The controller dynamically determines an optimal cruise control velocity from multiple candidate velocities based on real-time vehicle operating conditions, including drive unit efficiency maps, road grade, temperature, and altitude, thereby optimizing energy consumption while maintaining ease of operation.
Solution Approach 2:
The system changes the operating parameter (cruise control velocity) adaptively rather than maintaining a constant value. By selecting from multiple candidate velocities and adjusting the optimal velocity based on changing conditions such as road grade, temperature, and altitude, the system optimizes drive unit efficiency and energy consumption while preserving the simplicity of cruise control operation.
2Device complexity
If the vehicle operates at a fixed cruise control velocity, then the control system is simple, but the operable range is limited due to suboptimal efficiency
Solution Approach 1:
The cruise control system incorporates feedback mechanisms by continuously monitoring vehicle operating conditions (road grade, temperature, altitude) and using this information to dynamically select the optimal cruise control velocity from candidate velocities. This feedback loop enables the system to maintain higher efficiency across varying conditions, thereby extending the operable range without significantly increasing system complexity.
Solution Approach 2:
The system performs preliminary determination of multiple candidate velocities and identifies the optimal velocity before actual cruise control operation begins. By pre-calculating the optimal velocity based on current conditions and updating it as conditions change, the system maximizes efficiency and extends operable range while keeping the real-time control logic relatively simple.
3Use of energy by moving object
If cruise control selects from multiple candidate velocities, then the efficiency is optimized, but the control logic becomes more complex
Solution Approach 1:
The cruise control logic dynamically adapts by selecting from multiple candidate velocities based on real-time conditions. The system determines an optimal velocity from a set of candidates using efficiency maps and operating parameters, and updates this selection as conditions change, thereby optimizing drive unit efficiency while managing control logic complexity through structured dynamic adaptation.
4Loss of energy
If the cruise control velocity is adjusted based on real-time conditions, then the energy consumption is reduced, but the system requires continuous monitoring and adjustment
Solution Approach 1:
The system uses feedback from continuous monitoring of operating conditions (road grade, temperature, altitude) to dynamically adjust the optimal cruise control velocity. This feedback mechanism enables reduced energy consumption by adapting to real-time conditions while managing the complexity of continuous monitoring and adjustment through a structured control approach that updates the optimal velocity based on current sensor data.
Data Source
AI summary
A method includes receiving an eco-cruise control request that includes a requested cruise control velocity and a velocity tolerance. The eco-cruise control request instructs an drive unit to operate a vehicle at a velocity within the velocity tolerance of the requested cruise control velocity. The method also includes determining a range of candidate cruise control velocities that satisfy the velocity tolerance of the requested cruise control velocity. The method also includes determining an eco-cruise control velocity that maximizes a drive unit efficiency of the drive unit. Here, the eco-cruise control velocity includes one of the candidate cruise control velocities from the range of candidate cruise control velocities.