Vehicle Power Management Optimizing Fuel Efficiency via Route Data
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Solution Overview
Problem
Current methods for managing fuel consumption in automotive vehicles are imprecise, leading to suboptimal energy efficiency, as drivers lack precise control over power applied to the engine, which can be improved by considering external and internal vehicle parameters, command inputs, and operational parameters.
Innovation Solution
A power management system that calculates and optimizes the power applied to a vehicle engine using data from sensors, telemetries, memory, and user commands, incorporating external environment, vehicle status, and operational parameters to determine efficient speeds and power levels, which can be manually or automatically adjusted.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional cruise control systems are used to maintain constant vehicle speed, then ease of operation is improved, but fuel efficiency deteriorates because the system cannot optimize power consumption based on route conditions
Solution Approach 1:
The system receives and processes route information in advance before the vehicle travels the route. The power management device calculates optimal power consumption levels and speeds for upcoming route segments based on elevation changes, traffic conditions, and road geometry, allowing the vehicle to be pre-prepared for energy-efficient traversal of the entire route.
Solution Approach 2:
The system dynamically adjusts the vehicle's operating parameters (speed, power consumption) based on real-time route conditions and predicted future segments. Rather than maintaining a fixed constant speed, the cruise control adapts its setpoint continuously as the vehicle progresses through different route conditions, optimizing energy efficiency while maintaining ease of operation.
2Use of energy by moving object
If drivers manually control power applied to the engine to optimize fuel consumption, then fuel efficiency can be improved, but the precision and consistency of optimization deteriorates because drivers lack precise control mechanisms
Solution Approach 1:
The power management device continuously monitors actual vehicle performance, route conditions, and power consumption levels, then feeds this information back to adjust the optimal power consumption target. This closed-loop control enables precise and consistent optimization of fuel efficiency by automatically adjusting power application based on real-time feedback from sensors and route information systems.
3Use of energy by moving object
If a power management system with comprehensive route information processing is implemented, then fuel efficiency is improved by up to 10%, but device complexity increases due to additional sensors, processors, and control algorithms
Solution Approach 1:
The power management device performs multiple functions: it processes route information, calculates optimal power consumption levels, determines target speeds, controls the vehicle's cruise control system, and monitors actual performance. By consolidating these diverse functions into a single multi-functional control unit, the system achieves significant fuel efficiency improvements while minimizing the increase in overall device complexity.
Data Source
AI summary
A power management system includes a sensor interface that receives sensor data samples during operation of a vehicle. A storage device stores the sensor data samples for multiple points in time along a route segment traveled by the vehicle. One or more processors analyze the sensor data samples to detect a historical pattern of the vehicle. The one or more processors determine time efficient operational parameters for the vehicle in response to a destination and an estimated travel time to the destination. The estimated travel time may be based on predicted conditions of the vehicle indicated by the historical pattern. The time efficient operational parameters may be selected to decrease the estimated travel time. At least one of the sensor data samples may include telemetry data.