EV Power Management System Dynamic Speed Optimization
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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 conditions, driver inputs, and operational parameters.
Innovation Solution
A system comprising sensors, a processor, and memory that analyzes data to manage power consumption by calculating optimal power for the vehicle engine based on external environment, operational status, and command inputs, using power management logic to adjust speed and power application for improved fuel efficiency.
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 energy efficiency deteriorates because the systems do not optimize power consumption based on multiple factors
Solution Approach 1:
The system dynamically adjusts the vehicle speed setpoint based on real-time analysis of multiple factors including external environment (weather, traffic), internal vehicle conditions (battery state, motor efficiency), and route characteristics. This dynamic optimization allows the system to maintain ease of operation while continuously improving energy efficiency by adapting to changing conditions.
Solution Approach 2:
The system implements a closed-loop feedback mechanism that continuously monitors actual energy consumption, compares it with optimized targets, and adjusts control parameters accordingly. The feedback loop processes data from sensors, power management logic, and historical performance to refine speed recommendations and braking strategies, thereby improving energy efficiency while maintaining operational simplicity.
2Use of energy by moving object
If precise control of power consumption is implemented by analyzing multiple parameters, then energy efficiency is improved, but device complexity increases
Solution Approach 1:
The system employs a multi-functional power management controller that integrates multiple functions including speed optimization, energy consumption analysis, route planning, and braking control into a single device. This universal approach allows precise energy management without proportionally increasing system complexity, as one controller handles multiple tasks that would otherwise require separate systems.
Solution Approach 2:
The system utilizes existing vehicle sensors, processors, and communication buses to gather necessary data for power optimization, rather than requiring entirely new hardware. By leveraging already-present vehicle components and intelligence, the system achieves precise energy control with minimal additional complexity.
3Ease of operation
If operational assisting devices are added to provide additional control, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The system merges the functions of traditional cruise control with advanced power management and route optimization capabilities into a unified control system. By combining these functions, the system provides enhanced ease of operation through automated decision-making while avoiding the complexity increase that would result from adding separate operational assisting devices.
Data Source
AI summary
An apparatus comprising an interface, a memory and a processor. The interface may be configured to receive sensor data samples during operation of a vehicle. The memory may be configured to store the sensor data samples over a number of points in time. The processor may be configured to analyze the sensor data samples stored in the memory to detect a pattern. The processor may be configured to manage an application of brakes of the vehicle in response to the pattern.