Power Electronics SOC Prediction During Communication Loss
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Solution Overview
Problem
In electrified vehicles, a loss of communication between the traction battery controller and the power electronics module can disrupt power flow, leading to instability in battery state of charge (SOC) management, potentially causing propulsive force limitations and system inefficiencies.
Innovation Solution
A method is implemented where the battery control module periodically broadcasts SOC messages, and in the absence of these messages during key-on and torque demand states, the power flow is limited and diverted between accessory high-voltage loads and the electric powertrain to maintain SOC within predetermined ranges, minimizing power flow changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the battery control module and power electronics module maintain continuous communication for optimal power management, then SOC management precision is improved, but system reliability deteriorates due to vulnerability to communication loss
Solution Approach 1:
The power electronics module stores the last received SOC value and predicted SOC values in memory before communication loss occurs. This preliminary action enables the module to continue operating with stored data when communication is lost, maintaining both precision and reliability.
Solution Approach 2:
A predicted SOC value is introduced as an intermediary parameter that bridges the gap between actual SOC measurements and communication interruptions. The controller uses this predicted value to make power flow decisions during communication loss, preventing system shutdown while maintaining safe operation.
2Reliability
If power flow is restricted during communication loss to maintain safety, then system reliability is improved, but productivity deteriorates due to limited propulsive force
Solution Approach 1:
The power flow limit is dynamically adjusted based on the predicted SOC value rather than applying a fixed restriction. The controller continuously updates the power limit as the predicted SOC changes, allowing the vehicle to maintain maximum propulsive force when SOC is high while automatically reducing power when SOC decreases, thus balancing reliability and productivity.
Solution Approach 2:
The system changes the operational parameters by using predicted SOC values to adaptively modify power flow limits. This parameter change enables the system to transition from static safety restrictions to dynamic power management that responds to battery state predictions, maintaining both safety and performance.
3Object-affected harmful factors
If the system shuts down during communication loss to prevent battery damage, then battery protection is improved, but ease of operation deteriorates due to vehicle inoperability
Solution Approach 1:
The controller continuously monitors the predicted SOC value and provides feedback to adjust power flow limits in real-time. This feedback mechanism replaces the binary shutdown approach with continuous adaptive control, preventing battery damage through active management while keeping the vehicle operational.
Solution Approach 2:
The power electronics module autonomously manages power flow using its own predicted SOC calculations without requiring external communication. This self-service capability allows the vehicle to continue operating independently during communication loss, preventing battery damage while maintaining ease of operation.
Data Source
AI summary
A vehicle includes a battery control module and a controller. The battery control module is configured to issue at regular intervals a message indicative of a state of charge (SOC) of a battery. The controller is configured to, in an absence of receiving the messages at the regular intervals while in a key-on state and a torque demand is present, restrict power flow between the battery and an electric powertrain to a limit that is based on a predicted SOC to provide limited propulsive force.