Battery SoF Prediction with Dynamic Cranking Thresholds
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Solution Overview
Problem
Existing battery state-of-function (SoF) prediction methods are inadequate for accurately determining a vehicle's battery capability to restart the engine in stop-start systems, particularly under varying conditions due to aging and environmental factors, leading to potential engine shutdowns when the battery is still capable of starting the engine or excessive idling.
Innovation Solution
A system and method that includes a controller and memory to predict warm and cold cranking currents, calculating minimum battery voltages for engine cranking events, and using a dynamic histogram to adjust predictions based on real-time cranking current data, incorporating a correction factor to ensure accurate SoF assessment and prevent unnecessary engine shutdowns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed threshold method is used to predict battery SoF, then the prediction process is simple, but the prediction accuracy deteriorates under varying conditions such as aging and temperature changes
Solution Approach 1:
The patent applies dynamics by transitioning from fixed cranking current thresholds to dynamic thresholds that adapt based on engine temperature (cold vs. warm cranking) and battery aging state. The controller adjusts the threshold values according to real-time conditions, allowing the SoF prediction to remain accurate across varying operating conditions while maintaining a computationally simple implementation.
Solution Approach 2:
The patent changes the parameter thresholds based on the battery's aging state and temperature conditions. By storing multiple sets of cranking current thresholds corresponding to different battery health states and temperature ranges, the system selects appropriate thresholds dynamically, thereby maintaining high prediction accuracy without requiring complex real-time calculations.
2Loss of energy
If the engine is stopped frequently to conserve battery energy, then fuel consumption is reduced, but the reliability of the stop-start system deteriorates when the battery cannot restart the engine
Solution Approach 1:
The patent applies preliminary action by performing SoF prediction before the engine shutdown decision is made. The controller evaluates whether the battery has sufficient capacity to restart the engine under current and future conditions, and only permits shutdown when the prediction confirms adequate capacity. This prevents premature shutdowns that would lead to restart failures, thereby maintaining system reliability while still enabling energy conservation when appropriate.
Solution Approach 2:
The system uses feedback from real-time monitoring of battery parameters (voltage, current, temperature) and compares them against predicted SoF values to make informed shutdown decisions. The prediction algorithm continuously updates based on actual performance data, creating a closed-loop system that adjusts shutdown timing to maintain both energy efficiency and reliability.
3Device complexity
If warm and cold cranking events are treated identically, then the control logic is simple, but the SoF prediction accuracy deteriorates due to temperature variations
Solution Approach 1:
The patent segments cranking events into distinct categories based on engine temperature (cold cranking when engine temperature is below a threshold, warm cranking when above). Each segment has its own characteristic cranking current profile and threshold values stored in memory. The controller identifies the appropriate segment based on real-time temperature measurements and applies the corresponding threshold set, thereby accounting for temperature effects while maintaining relatively simple control logic through pre-characterized segments.
Data Source
AI summary
A system for a vehicle having an engine and a battery includes a memory and a controller. The memory has a first current expected to be provided by the battery for restarting the engine during a warm cranking event and a second current expected to be provided by the battery for restarting the engine during a cold cranking event. The controller to predict a first minimum voltage of the battery expected during the warm cranking event based on the first current and a second minimum voltage of the battery expected during the cold cranking event based on the second current.