Electric Vehicle Energy Autonomy Management System
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Solution Overview
Problem
The limited autonomy of electric vehicles due to costly, large, and heavy batteries, combined with the scarcity of charging stations and unpredictable recharging times, creates uncertainty for users regarding their ability to reach destinations, especially in variable traffic conditions.
Innovation Solution
An electronic system that automatically manages energy autonomy by using sensors to monitor drive parameters and energy capacity, coupled with a central control unit and user interface, which calculates and adjusts torque requests based on the path, speed, acceleration, and energy capacity to ensure journey completion, providing real-time warnings and optimizing energy use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If batteries are made larger and heavier to ensure sufficient energy supply for suitable performances, then energy capacity is improved, but vehicle weight and cost increase
Solution Approach 1:
The system performs preliminary calculations of energy consumption for the entire path before the journey begins, and continuously monitors energy capacity during the journey. By predicting future energy needs based on pre-calculated consumption patterns for different road sections, the system can alert the driver in advance when energy capacity becomes insufficient, allowing time to take corrective actions such as finding charging stations or adjusting driving behavior.
Solution Approach 2:
The system implements continuous feedback by monitoring actual energy consumption during the journey and comparing it with predicted consumption. The control unit receives real-time data from sensors about drive parameters and energy capacity, recalculates allowable variations, and adjusts warnings or recommendations dynamically. This closed-loop feedback enables the system to adapt to actual driving conditions and provide accurate guidance for maintaining sufficient energy capacity.
2Device complexity
If average consumption hypotheses are used to indicate travel distance, then system complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The system divides the travel path into multiple space intervals and calculates energy consumption separately for each interval based on specific characteristics such as road slope, traffic conditions, and driving style. Instead of using a single average consumption value for the entire journey, the system segments the path and sums the energy requirements of individual segments, providing a much more accurate prediction of total energy consumption and remaining travel distance.
Solution Approach 2:
The system dynamically changes consumption parameters based on actual driving conditions detected by sensors. Instead of using fixed average consumption values, the system adjusts consumption rates according to real-time parameters such as acceleration, speed, road gradient, and traffic conditions. This allows the system to maintain high measurement precision while adapting to varying operational conditions throughout the journey.
3Reliability
If real-time monitoring and dynamic adjustment of torque requests are implemented, then journey completion reliability is improved, but device complexity increases
Solution Approach 1:
The control unit performs multiple functions using a single integrated system: it monitors energy capacity from sensors, calculates energy consumption for path segments, determines allowable energy variations, generates torque requests, and provides user warnings. By consolidating these functions into one multi-functional control unit rather than separate dedicated systems for each function, the patent improves journey completion reliability while minimizing the increase in device complexity.
Solution Approach 2:
The system automatically monitors its own energy status and self-regulates torque requests without requiring external intervention. The control unit continuously calculates energy capacity, compares it with predicted consumption, determines when energy becomes insufficient, and autonomously adjusts torque requests or issues warnings to the driver. This self-service capability ensures journey completion reliability while avoiding the need for additional complex external control systems.
Data Source
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AI summary
A method (100) is described for the automatic management of the energy autonomy of a vehicle of the type comprising a torque-controllable motor (21), a plurality of sensors (22) for the instantaneous measurement of a plurality of drive parameters and of energy capacity (C) of such a vehicle, and a first central control unit (23) coupled with the motor (21), capable of generating an instantaneous torque request (md) on the basis of a request of a user. The method (100) comprises the phases of receiving (101) from an interface means (11) a signal for indicating a distance and/or a path to cover, and dividing the distance and/or the path into a plurality of space intervals; calculating (102) an allowable variation of energy capacity (AC) in a space interval on the basis of an energy capacity (C) detected by the plurality of sensors (22) and on the basis of variation laws of the energy capacity (C); determining (103) limit conditions for the speed and/or acceleration of the vehicle (20), on the basis of a map, chosen among a plurality of maps of speed-acceleration-variation of energy capacity; generating (110) a regulated instantaneous torque request (m) on the basis of the speed and/or acceleration detected by the plurality of sensors (22), of the determined limit conditions for the speed and/or acceleration and of the instantaneous torque request (md) generated by the first central control unit (23). Moreover, an electronic system (10) capable of implementing such a method is described.