Following Drive Control Using Multi-Parameter Energy Estimation
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Solution Overview
Problem
Conventional vehicle driver-assistance devices inaccurately estimate energy consumption by considering only air resistance, failing to account for other parameters that affect energy consumption, such as road gradient, vehicle weight, and electric power usage.
Innovation Solution
The device acquires energy consumption amounts by considering additional parameters like road gradient, vehicle weight, and electric power consumption, alongside air resistance, to accurately select and execute energy-efficient driving control strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If energy consumption is calculated based only on air resistance, then the calculation process is simple, but the energy consumption estimation is inaccurate
Solution Approach 1:
The energy consumption calculation is segmented into multiple independent components: air resistance component, gradient resistance component, rolling resistance component, and acceleration resistance component. Each component is calculated separately using specific parameters, and then summed to obtain the total energy consumption. This segmentation allows for accurate estimation while keeping each calculation module simple and manageable.
Solution Approach 2:
The control device integrates multiple measurement functions into a single system that simultaneously measures air resistance, gradient, vehicle weight, and acceleration parameters. This multi-functional approach enables comprehensive energy consumption estimation without requiring separate complex measurement systems for each parameter.
2Measurement precision
If multiple parameters are considered for energy consumption calculation, then the energy consumption estimation becomes accurate, but the calculation complexity increases
Solution Approach 1:
The control device utilizes existing vehicle sensors and control systems to obtain measurement data. The air resistance is derived from the air conditioner compressor operation data, gradient from the navigation system, weight from the suspension system sensors, and acceleration from the existing acceleration sensor. This self-service approach allows accurate multi-parameter measurement without adding complex external detection systems.
3Productivity
If comprehensive parameters are used for energy consumption calculation, then the driving control selection is optimized, but the processing time increases
Solution Approach 1:
The control device pre-calculates and stores the energy consumption characteristics for different driving modes (first following drive control and second following drive control) based on the current vehicle state and environmental parameters. When selecting driving control, it compares the pre-calculated energy consumption values to quickly determine the more efficient option, reducing real-time processing time while maintaining comprehensive parameter analysis.
Data Source
AI summary
A vehicle driver-assistance device selectively executes first following drive control and second following drive control. The vehicle driver-assistance device acquires an energy consumption amount when it is assumed that each of the first following drive control and the second following drive control has been executed, based on at least one of the air resistance of the own vehicle, the gradient of a road on which the own vehicle is scheduled to travel, the weight of the own vehicle, and the amount of electric power consumed by the own vehicle, and executes the control out of the first following drive control and the second following drive control that consumes less energy.