BEV Life Support Controller Probability Calculation
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Solution Overview
Problem
Operators of battery electric vehicles (BEVs) face the risk of becoming stranded due to depleted batteries, particularly problematic for those with special needs, as existing range estimation algorithms do not effectively provide data on the likelihood of reaching a charging station based on the vehicle's state of charge.
Innovation Solution
A BEV life support system that includes a controller receiving charging station location data and state of charge data from the vehicle battery, determining the probability of reaching a charging station, and communicating this probability to the operator, allowing them to decide whether to continue driving or safely stop and request assistance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If range estimation algorithms are used to predict state of charge and future energy consumption, then the system can predict the likelihood of reaching a destination, but the system cannot provide actionable guidance for operators facing battery depletion with special needs
Solution Approach 1:
The system performs preliminary identification of charging stations within the vehicle's range before the operator needs to make a decision. By pre-calculating which charging stations are accessible based on current state of charge and predicted consumption, the system prepares actionable information in advance, enabling operators to make informed decisions about whether to continue driving or seek assistance.
Solution Approach 2:
The system provides feedback to the operator about the likelihood of reaching charging stations based on real-time state of charge data and predicted energy consumption. This feedback loop transforms abstract range estimates into concrete probability information, allowing operators to understand their situation and make informed decisions about continuing operation or requesting help.
2Reliability
If the system provides detailed probability data about reaching charging stations, then operators can make informed decisions, but the system complexity increases
Solution Approach 1:
The controller performs multiple functions using the same hardware components: it manages standard vehicle control operations, processes state of charge data, predicts future energy consumption, identifies charging stations, and generates probability assessments. By making the controller multi-functional, the system provides comprehensive decision-support capabilities without requiring separate dedicated hardware for each function.
Solution Approach 2:
The system combines range estimation algorithms, state of charge monitoring, charging station location data, and probability calculation into a single integrated decision-support system. By merging these previously separate functions into one cohesive system, the patent reduces overall complexity while maintaining the reliability needed for operators to make informed decisions.
Data Source
AI summary
A battery electric vehicle life support system for a battery electric vehicle. The system may include at least one controller adapted to receive charging station location data; a vehicle battery interfacing with the at least one controller, the at least one controller adapted to receive state of charge data from the vehicle battery; and the at least one controller adapted to determine a probability that the vehicle will reach at least one battery charging station based on the state of charge data and the charging station location data. A battery electric vehicle life support method is also disclosed.