Hybrid Vehicle Power Split Control Using Route-Based Battery SOC
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Solution Overview
Problem
Current hybrid vehicle control methods are inefficient in reducing fuel consumption and greenhouse gas emissions, as they rely on a greedy approach that depletes the battery without considering the entire route's parameters, leading to suboptimal energy usage between the electric motor and fuel engine.
Innovation Solution
A method that computes a state of charge for the battery along a planned route by distributing the use of the electric motor and fuel engine, allowing priority use of the fuel engine to decrease fuel consumption, using optimization techniques like Pontryagin Maximization Principle to generate control instructions that optimize energy usage based on route parameters and geofence constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the electric motor is used first and the battery is depleted as much as possible, then the implementation is simple, but the fuel consumption and greenhouse gas emissions cannot be further decreased
Solution Approach 1:
The system performs preliminary computation of the state of charge along the planned route before actual vehicle operation. By calculating the optimal battery charge distribution in advance based on route parameters, the system enables optimized power split decisions during driving, thereby reducing overall fuel consumption while maintaining simple real-time control implementation
Solution Approach 2:
The system dynamically adjusts the power split between electric motor and fuel engine based on computed state of charge profiles. Instead of fixed greedy control, the control strategy adapts to route-specific conditions by varying the battery discharge/charge schedule, optimizing energy usage while keeping the control logic manageable through pre-computation
2Device complexity
If the electric motor is used first to deplete the battery, then the control strategy is simple, but the overall energy optimization over the planned route is suboptimal
Solution Approach 1:
The system performs preliminary computation of the state of charge along the planned route before actual vehicle operation. By calculating the optimal battery charge distribution in advance based on route parameters, the system enables optimized power split decisions during driving, thereby reducing overall fuel consumption while maintaining simple real-time control implementation
Solution Approach 2:
The control system uses pre-computed state of charge information to automatically make optimal power split decisions without requiring complex real-time optimization calculations. The system serves itself by using advance route analysis to guide runtime control, achieving high energy efficiency with minimal computational burden during actual driving
3Use of energy by moving object
If priority use of the fuel engine is allowed over battery depletion, then the fuel consumption decreases, but the battery state of charge management becomes more complex
Solution Approach 1:
The system performs preliminary computation of the state of charge along the planned route before actual vehicle operation. By calculating the optimal battery charge distribution in advance based on route parameters, the system enables optimized power split decisions during driving, thereby reducing overall fuel consumption while maintaining simple real-time control implementation
Solution Approach 2:
The pre-computed state of charge profile acts as an intermediary that translates complex route optimization problems into simple runtime control decisions. Instead of making complex real-time decisions about when to use the engine or battery, the system follows the pre-determined SOC profile, which mediates between fuel consumption optimization and control simplicity
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 reduces fuel consumption and greenhouse gas emissions by optimizing energy usage, ensuring the battery is depleted as much as possible while using the electric motor efficiently, and adhering to environmental constraints, resulting in lower fuel consumption and emissions compared to traditional methods.
Implementation Method 1
an electric motor configured to supply mechanical power to the drive train using power from the battery
Implementation Method 2
a fuel engine configured to supply mechanical power to the drive train or to supply electrical power to the battery
Implementation Method 3
a battery, an electric motor powered by the battery
Data Source
Figure 1
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AI summary
A method of generating control instructions for a hybrid vehicle comprising a drive train, a battery, an electric motor powered by the battery and a fuel engine, wherein the electric motor and the fuel engine are configured to supply mechanical power to the drive train, the method comprising: - obtaining a planned route of the vehicle; - computing a state of charge of the battery along the planned route, wherein the state of charge is determined by distributing use of the electric motor over the planned route while allowing priority use of the fuel engine over depletion of the battery to decrease fuel consumption of the fuel engine over the planned route; - outputting control instructions for the vehicle to follow the computed state of charge along the planned route.