Hybrid Vehicle Power Apportionment via Cost-Weighted Control
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Solution Overview
Problem
There is a need for improved methods and apparatus to manage power in hybrid vehicles, which typically consist of an engine, an electric motor, and an energy storage element, to minimize fuel consumption and operating costs while maintaining efficient vehicle operation.
Innovation Solution
A method and apparatus that select the optimal apportionment of power between the engine and the electric motor based on fuel prices and storage element replacement prices, using a processor circuit to calculate and adjust operating costs, including engine fuel consumption and storage element lifetime costs, and generate control signals to manage power distribution accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If power is apportioned between engine and motor to minimize fuel consumption, then fuel efficiency improves, but operating cost management becomes complex
Solution Approach 1:
The system dynamically changes operating parameters (power apportionment between engine and motor) based on real-time conditions such as fuel prices and storage element replacement prices. The controller adjusts the cost-weighted power distribution strategy by modifying parameters like the cost of fuel consumption and cost of storage element wear, allowing optimal power management without excessive complexity.
2Duration of action of stationary object
If storage element lifetime cost is included in operating cost calculation, then long-term efficiency improves, but calculation complexity increases
Solution Approach 1:
The controller acts as an intermediary that simplifies the complex relationship between power apportionment and storage element lifetime. It calculates storage element lifetime cost as a separate weighted parameter based on power drawn from or charged to the storage element, then integrates this into the overall operating cost function. This mediator approach breaks down the complex lifetime prediction into manageable computational steps.
3Reliability
If relative weighting between fuel consumption cost and storage element lifetime cost is adjusted dynamically, then operating cost optimization improves, but control system complexity increases
Solution Approach 1:
The system dynamically adjusts the relative weighting between fuel consumption cost and storage element lifetime cost based on real-time operating conditions. The controller modifies these weights according to factors such as current fuel prices, storage element state of charge, temperature, and power demand conditions. This dynamic adaptation allows the system to optimize operating costs under varying conditions without requiring a completely complex control architecture.
Data Source
AI summary
A method and apparatus for managing power in a hybrid vehicle is disclosed. The vehicle includes an engine, an electric motor, and an energy storage element coupled to the motor. The method involves receiving a request to supply operating power to drive the vehicle and responding to the request by selecting an apportionment of operating power between the engine and the motor from among a plurality of apportionments having respective operating costs such that the selected apportionment is associated with a minimum operating cost, the operating cost including at least an engine fuel consumption cost and a storage element lifetime cost. The method further involves causing power to be supplied by at least one of the engine and the motor in accordance with the selected apportionment.