Predictive Battery Cooling for Route-Based Thermal Peaks
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Solution Overview
Problem
In electrified vehicles, the battery cooling system often fails to maintain battery temperature below a threshold, leading to reduced traction and accessory power, which increases fuel consumption and reduces the electric range, thereby diminishing the benefits of electrification.
Innovation Solution
A method is developed to predict battery temperature along a vehicle route, determining a confidence level, and preemptively increasing battery cooling when the predicted temperature exceeds a threshold, ensuring the battery remains within safe limits while optimizing coolant availability for other systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the battery cooling system operates at maximum capacity continuously, then the battery temperature remains below the upper threshold, but the electric range is reduced and fuel consumption increases
Solution Approach 1:
The system performs preliminary cooling of the battery before high-power events occur by detecting predicted high-power events from driver behavior patterns, environmental conditions, and route information. The controller increases coolant flow rate to the battery in advance, preventing temperature rise before it occurs, which eliminates the need for continuous maximum-capacity cooling operation.
Solution Approach 2:
The system continuously monitors actual battery temperature, coolant temperature, and coolant flow rate, comparing these against predicted values. When deviations are detected or when high-power events are predicted based on sensor inputs (accelerator pedal position, ambient temperature, humidity), the controller dynamically adjusts coolant flow rate to maintain optimal battery temperature while minimizing energy consumption.
2Adaptability or versatility
If the battery cooling system shares coolant with auxiliary systems, then cooling capacity is distributed, but the battery temperature may exceed the threshold when cooling demand is high
Solution Approach 1:
The system predicts high-power events before they occur by analyzing driver behavior patterns, environmental conditions, and route information. When a high-power event is predicted, the controller preemptively increases coolant flow rate to the battery, ensuring sufficient cooling capacity is allocated before the thermal load increases, thereby maintaining battery temperature control while still sharing the coolant system with auxiliary systems.
Solution Approach 2:
The controller dynamically adjusts the coolant flow rate to the battery based on real-time conditions including predicted power demand, actual battery temperature, coolant temperature, and environmental factors. This dynamic adjustment allows the system to optimize coolant distribution between the battery and auxiliary systems, ensuring the battery receives sufficient cooling when needed while maintaining system versatility.
3Reliability
If preemptive cooling is applied, then cooling demands at upcoming locations are reduced, but the device complexity increases due to prediction and confidence level determination
Solution Approach 1:
The controller utilizes existing sensors already present in the vehicle (accelerator pedal position sensor, ambient temperature sensor, humidity sensor) and existing data structures (route information, predicted power events) to perform temperature prediction and confidence level determination. By repurposing existing system components for the prediction function, the system achieves reliable battery temperature control without adding significant device complexity.
Solution Approach 2:
The system uses the vehicle's existing communication networks and control modules to share data between the prediction algorithm and the cooling control system. The controller self-manages the coordination between predicted thermal events and coolant flow adjustments, eliminating the need for separate dedicated prediction hardware and reducing overall system complexity.
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 maintains battery temperature below the threshold, reduces cooling demands at critical locations, and enhances overall vehicle performance by ensuring sufficient cooling capacity for both the battery and auxiliary systems, thereby improving customer satisfaction and reducing fuel consumption.
Implementation Method 1
the battery cooling system may not be able to maintain the battery temperature below the upper threshold
Implementation Method 2
increasing coolant flow rate to the battery
Data Source
AI summary
Methods and systems are provided for a battery thermal management system. In one example, a method includes increasing coolant to a battery above a currently demanded battery cooling in response to a predicted battery temperature exceeding a threshold temperature at an upcoming location.