Hybrid Drive Control Strategy for Special Function Execution
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Solution Overview
Problem
Hybrid drive systems in motor vehicles face challenges in incorporating special function requests, such as diagnostic and calibration functions, into their energy optimization methods, as these functions often require operating states that deviate from the optimized energy usage settings, leading to inefficient energy use and emission issues.
Innovation Solution
A method is introduced to create an overall cost function that accounts for special function requests by assigning partial cost functions based on priority, allowing for the optimization of the operating point to accommodate these functions, ensuring their execution while minimizing energy usage and emissions. This involves determining an optimized operating point that considers the load distribution and rotational speed of the hybrid drive system, enabling the execution of special functions like catalytic converter heating and diagnostic tasks within specific operating ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the hybrid drive system operates strictly according to energy minimization optimization, then energy usage is minimized, but special functions (diagnostic, calibration, component protection) cannot be executed within required timeframes
Solution Approach 1:
The cost function is made dynamic by incorporating time-dependent partial cost functions for special functions. The optimization continuously adapts the operating point based on current special function requests, allowing the system to switch between energy optimization and special function execution modes seamlessly. This dynamic adjustment resolves the contradiction by making the system responsive to both energy efficiency and reliability requirements at different moments.
Solution Approach 2:
The system performs preliminary assessment of special function requests by evaluating partial cost functions before finalizing the operating point. By anticipating special function needs and incorporating them into the cost function in advance, the system can proactively adjust the operating point to enable timely execution of diagnostic, calibration, or component protection functions while minimizing energy impact.
2Reliability
If the system executes special functions frequently to ensure reliability, then special function requirements are met, but energy usage increases and emissions rise
Solution Approach 1:
The system changes the parameters of the cost function by introducing partial cost functions that quantify the energy and emission penalties associated with executing special functions. By adjusting these partial cost parameters based on the urgency and importance of special functions, the optimization can determine the most energy-efficient timing and operating conditions for executing special functions, thus reducing overall energy loss while maintaining reliability.
Solution Approach 2:
The system selectively executes special functions only when necessary and when the optimized operating point indicates it is energy-efficient to do so. By skipping unnecessary or low-priority special function executions and rushing through only the critical ones at optimally chosen moments, the system minimizes energy loss and emissions while still meeting essential reliability requirements.
3Reliability
If the hybrid drive system adapts operating point for special functions, then special functions can be executed, but the general energy minimization optimization is compromised
Solution Approach 1:
The system merges the energy minimization objective with special function execution requirements by combining the base cost function with partial cost functions for special functions into a unified overall cost function. This merging allows the optimization to simultaneously consider both energy efficiency and special function needs, finding operating points that balance both objectives rather than treating them as separate conflicting goals.
Solution Approach 2:
The cost function is designed to be universal by incorporating multiple partial cost functions that can handle different types of special functions (diagnostic, calibration, component protection) through a unified optimization framework. This multi-functional cost function structure allows the same optimization mechanism to serve both energy minimization and diverse special function execution requirements, maintaining productivity while enabling reliability.
Data Source
AI summary
A method for operating a hybrid drive system which includes ascertaining an overall cost function that takes into account the cost function, which is a function of the operating point, for minimizing an energy usage of the hybrid drive system, and that takes into account one or more partial cost functions, which are a function of the operating point, which are each assigned to a requested special function; determining an optimized operating point of the hybrid drive system corresponding to an optimization according to the ascertained overall cost function; operating of the hybrid drive system at the operating point; and executing of those of the requested special functions for which the determined operating point is within an operating range assigned to the respective special function.