Predictive Battery Thermal Management for Electric Vehicles
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Solution Overview
Problem
Traditional battery thermal management systems in electric vehicles consume excessive power, limiting the vehicle's range due to their inability to efficiently predict and manage battery temperature during varying driving conditions, often requiring suboptimal cooling settings to prevent overheating.
Innovation Solution
A method and system that determine a battery cooling profile based on route information and current battery status, identifying regions where natural cooling occurs to minimize active cooling, allowing the battery to operate closer to its upper temperature limit, thereby reducing power consumption by optimizing cooling only when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional battery thermal management systems maintain battery temperature at a specified level without considering external parameters, then battery temperature stays within limits, but power consumption of the cooling system increases
Solution Approach 1:
The system performs preliminary analysis of the driving cycle and predicts battery temperature evolution before the actual driving occurs. This allows the thermal management system to proactively adjust cooling strategies in advance, avoiding excessive cooling during periods when it would be unnecessary, thereby reducing power consumption while maintaining temperature reliability
Solution Approach 2:
The cooling system transitions from a static temperature maintenance approach to a dynamic, adaptive control strategy. The cooling power and activation are continuously adjusted based on real-time battery status, driving cycle characteristics, and predicted temperature profiles, allowing the system to optimize power consumption while maintaining temperature within acceptable limits
2Reliability
If battery temperature setpoint is selected well below the upper limit to account for transients, then temperature stays within limits during aggressive acceleration and deceleration, but cooling power consumption increases
Solution Approach 1:
The system analyzes the driving cycle in advance to identify transient periods such as aggressive acceleration and deceleration. By predicting these transients beforehand, the system can temporarily adjust the temperature setpoint closer to the upper limit during stable periods while maintaining adequate margins during predicted transients, thereby reducing overall cooling power consumption without compromising temperature stability when needed
Solution Approach 2:
The temperature setpoint is dynamically adjusted based on driving conditions rather than maintaining a fixed conservative value. The system modifies the setpoint parameter in real-time according to the actual driving cycle characteristics, allowing higher setpoints during low-stress periods and lower setpoints during high-stress transients, optimizing the balance between temperature reliability and cooling energy consumption
Data Source
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AI summary
A method for controlling cooling of a traction battery in an electric vehicle where the method comprises determining a battery temperature profile for a segment of a planned route based on route information describing a route from a starting point to a destination and based on a current battery status and determining a battery cooling profile for the segment of the route based on the battery temperature profile. By means of the route information and the state of the battery, the battery cooling profile can be determined in order to minimize the power required for cooling the battery. Since the route information can provide information relating to a range of parameters which influence the power consumption along the route, the cooling needs of the battery can also be estimated for the route as a whole.