EV Battery Temperature Regulation Using Route-Based Thermal Prediction
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Solution Overview
Problem
Inadequate thermal management of electric vehicle battery cells leads to reduced performance, driving range, and battery life due to temperature fluctuations during propulsion and regenerative braking events, causing inefficiencies and potential thermal runaway.
Innovation Solution
A predictive temperature regulation system that adjusts battery cell temperatures based on route projections, using data such as road speed, terrain elevation, ambient temperature, and traffic data to maintain optimal operating conditions, preventing excessive heating or cooling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If battery cell temperatures are regulated to optimal operating conditions by predicting future thermal demand along a route projection, then thermal efficiency and battery performance are improved, but device complexity and computational requirements increase
Solution Approach 1:
The system performs preliminary thermal management actions by predicting future thermal demand along a route projection and preemptively adjusting battery cell temperatures to desired setpoints before thermal events occur. This allows the battery to maintain optimal operating conditions during propulsion and regenerative braking events without reactive temperature control, improving performance consistency while using forecast-based planning.
Solution Approach 2:
The thermal management system dynamically adjusts battery cell temperatures based on predicted thermal demand from route projections, ambient temperature forecasts, and vehicle operating conditions. The system continuously monitors and modifies cooling/heating strategies in real-time according to forecasted thermal events, transforming a static thermal control system into an adaptive, dynamic one that responds to predicted conditions.
2Duration of action of stationary object
If battery cell temperatures are adjusted preemptively to prevent exceeding temperature thresholds, then battery degradation is reduced and battery life is extended, but energy consumption increases due to additional heating or cooling operations
Solution Approach 1:
The system preemptively adjusts battery cell temperatures before thermal events occur by analyzing predicted thermal demand along the route. When high thermal loading events are forecasted, the system pre-cools the battery to lower setpoints. When low thermal loading is predicted, the system pre-heats to ensure optimal operating temperature, thereby extending battery life while managing energy consumption through forecast-based planning.
Solution Approach 2:
The system changes temperature setpoint parameters dynamically based on predicted thermal conditions. Instead of maintaining a fixed temperature setpoint, the system adjusts the target temperature range according to forecasted propulsion and regenerative braking events, ambient temperature predictions, and route characteristics, optimizing the balance between battery life extension and energy consumption.
3Productivity
If thermal management systems use active cooling or heating to maintain ideal temperature ranges, then battery performance is optimized, but the system complexity and energy requirements increase
Solution Approach 1:
The system uses predicted thermal demand information to preemptively adjust battery cell temperatures to desired setpoints before charging or high-power discharge events. By forecasting thermal events along the route projection and ambient temperature conditions, the system prepares the battery in advance, enabling faster charging speeds when needed while reducing the need for intensive active cooling during charging operations.
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 enhances thermal efficiency, reduces battery degradation, and improves driving performance and consistency, extending battery life and reducing the need for excessive battery capacity, thereby lowering environmental impact.
Implementation Method 1
These systems employ various techniques such as active cooling or heating, liquid or air cooling, and intelligent temperature control algorithms.
Implementation Method 2
These systems employ various techniques such as active cooling or heating, liquid or air cooling, and intelligent temperature control algorithms.
Implementation Method 3
These systems employ various techniques such as active cooling or heating, liquid or air cooling, and intelligent temperature control algorithms.
Data Source
AI summary
Aspects of the subject disclosure relate to predictive vehicle battery temperature regulation. A device implementing the subject technology may include a processor configured to obtain different types of data associated with a route projection of a vehicle. The processor can determine a thermal demand projection of the vehicle that maps to the route projection based on the different types of data. The processor also can adjust a temperature of a battery of the vehicle to within a predefined temperature range based on the thermal demand projection for the route projection.