Electric Vehicle Energy Management Using Actual Mass and Drag
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Solution Overview
Problem
Existing methods for optimizing the operating strategy of electric vehicles do not account for variations in vehicle mass and air resistance coefficients, leading to suboptimal energy recovery during deceleration and increased brake sizes, as well as reduced traveling range due to inefficient energy management.
Innovation Solution
A method that calculates and adjusts the target charging state and operating strategy for electric vehicles based on predicted route conditions, including total vehicle mass and air resistance coefficients, to maximize energy absorption through recuperative deceleration, allowing for efficient energy management and reduced brake size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a predetermined normal value for vehicle mass and air resistance coefficient is used for energy management, then the control system is simple, but the energy recovery during deceleration is suboptimal and brake size increases
Solution Approach 1:
The system performs preliminary determination of the actual vehicle mass and air resistance coefficient before the trip begins. This advance calculation allows the energy management system to be optimized based on real vehicle conditions rather than predetermined normal values, maximizing energy recovery potential during deceleration phases.
Solution Approach 2:
The system dynamically changes the parameters used for energy management from fixed predetermined normal values to actual measured values of vehicle mass and air resistance coefficient. This parameter adaptation enables accurate calculation of recuperative energy potential and optimizes the target charging state determination based on real vehicle characteristics.
2Ease of operation
If a predetermined normal value for vehicle mass and air resistance coefficient is used, then the system is easy to operate, but the traveling range is reduced due to inefficient energy management
Solution Approach 1:
The system performs preliminary determination of the actual vehicle mass and air resistance coefficient before the trip begins. This advance calculation allows the energy management system to be optimized based on real vehicle conditions rather than predetermined normal values, maximizing energy recovery potential during deceleration phases.
Solution Approach 2:
The system uses actual measured values of vehicle mass and air resistance coefficient to provide feedback for optimizing the target charging state determination. This feedback mechanism ensures that the energy management strategy adapts to real vehicle conditions, improving traveling range through efficient energy utilization.
3Loss of energy
If actual vehicle mass and air resistance coefficient are determined, then energy absorption during deceleration is optimized, but the calculation complexity increases
Solution Approach 1:
The system performs preliminary determination of the actual vehicle mass and air resistance coefficient before the trip begins. This advance calculation allows the energy management system to be optimized based on real vehicle conditions rather than predetermined normal values, maximizing energy recovery potential during deceleration phases.
Solution Approach 2:
The system dynamically changes the parameters used for energy management from fixed predetermined normal values to actual measured values of vehicle mass and air resistance coefficient. This parameter adaptation enables accurate calculation of recuperative energy potential and optimizes the target charging state determination based on real vehicle characteristics.
4Use of energy by moving object
If actual vehicle mass and air resistance coefficient are determined, then traveling range is enhanced, but the computational requirements increase
Solution Approach 1:
The system performs preliminary determination of the actual vehicle mass and air resistance coefficient before the trip begins. This advance calculation allows the energy management system to be optimized based on real vehicle conditions rather than predetermined normal values, maximizing energy recovery potential during deceleration phases.
Solution Approach 2:
The system uses actual measured values of vehicle mass and air resistance coefficient to provide feedback for optimizing the target charging state determination. This feedback mechanism ensures that the energy management strategy adapts to real vehicle conditions, improving traveling range through efficient energy utilization.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables optimal energy absorption and reduced brake size, enhancing the electric vehicle's traveling range and efficiency by accurately accounting for varying conditions during deceleration processes.
Implementation Method 1
electrical energy obtainable with a predetermined minimum amount from recuperative deceleration along this route during each deceleration process
Data Source
AI summary
A method for operating an electrically operated or also electrically operable motor vehicle provided with a rechargeable electric energy storage device associated with the drive motor of the motor vehicle. A target charging state is determined for the energy storage device and an operating strategy is determined for a route that is calculated, entered or predicted for the next trip, by which recuperative deceleration is enabled with a specifiable minimum amount for deceleration processes occurring along the route.


