Hybrid Battery Conditioning for Forecast-Based Cold Start Control
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Solution Overview
Problem
Current high voltage (48V) batteries in hybrid electric vehicles struggle to meet stringent emissions standards like EU7 due to insufficient discharge capability, which is influenced by cell temperature, state of charge, and battery age, leading to compromised HEV functions and increased engine run-on times.
Innovation Solution
A battery control strategy that utilizes forecast weather information and operational parameters to optimize state of charge targets, prioritizing HEV functions and emissions support, allowing existing batteries to be retroactively updated via over-the-air updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the battery state of charge is maintained at high levels to ensure sufficient discharge capability for emissions standards, then the battery can meet EU7 tailpipe requirements, but the battery energy throughput increases and battery life decreases
Solution Approach 1:
The system performs preliminary battery conditioning by forecasting future weather conditions and proactively adjusting the battery state of charge before cold start events occur. This allows the battery to be prepared in advance for emissions compliance without continuously maintaining high charge levels, thereby reducing unnecessary energy throughput and extending battery life.
Solution Approach 2:
The control strategy dynamically adjusts battery management parameters based on real-time weather forecasts, navigation data, and predicted drive cycles. Instead of using static worst-case assumptions, the system adapts the state of charge targets and conditioning strategies to match actual predicted conditions, optimizing the balance between emissions compliance and battery durability.
2Adaptability or versatility
If the battery is conditioned to maintain sufficient discharge capability for all possible scenarios, then the battery can support HEV functions and emissions requirements, but the battery energy throughput increases unnecessarily in mild conditions
Solution Approach 1:
The system applies different battery conditioning strategies tailored to specific predicted scenarios rather than using a uniform approach. Based on forecasted weather conditions, navigation routes, and drive cycle predictions, the control strategy adjusts state of charge targets and conditioning intensity locally for each predicted operating condition, ensuring adequate battery capability only when and where needed.
Solution Approach 2:
The control strategy changes key battery parameters such as state of charge targets, charge/discharge rates, and conditioning thresholds based on predicted operating conditions. By dynamically adjusting these parameters according to weather forecasts and drive cycle predictions, the system maintains adequate battery capability while minimizing unnecessary energy throughput in mild conditions.
3Ease of manufacture
If existing 48V batteries are used to meet EU7 start sequence requirements, then packaging constraints and cost are satisfied, but the batteries lack sufficient discharge capability in cold conditions without additional energy reserves
Solution Approach 1:
The system performs preliminary battery conditioning and energy reservation based on forecasted cold start events. By proactively managing the battery state of charge in anticipation of future cold conditions, the system ensures that existing 48V batteries have sufficient discharge capability when needed, without requiring larger battery packs or additional energy reserves.
Solution Approach 2:
The control strategy adjusts battery operating parameters such as state of charge targets, temperature management, and discharge rate limits based on predicted environmental conditions and battery age. These parameter changes enable existing batteries to deliver adequate power for cold start sequences without requiring hardware modifications or additional energy capacity.
Data Source
AI summary
Methods and system are provided to select a battery control strategy for a hybrid battery of a hybrid electric vehicle. The methods comprise receiving forecast weather information at a first location, determining an operational parameter of the hybrid battery, and selecting a first battery control strategy based on the forecast weather information and the operational parameter of the hybrid battery, wherein the control strategy comprises a state of charge target for the hybrid battery required for a next start sequence.