Hybrid Engine Torque Deviation Learning for Full Load Transition

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Solution Overview

Problem

Hybrid electric vehicles face inefficiencies in determining the transition to full load mode due to inaccuracies in calculating engine part load maximum output torque, leading to increased fuel consumption and decreased driving efficiency between hybrid control unit (HCU) and engine management system (EMS) discrepancies.

Innovation Solution

An apparatus and method that calculate engine part load maximum output torque by learning torque deviation, using a torque deviation calculating unit, engine output change learning unit, and engine part load maximum output torque calculating unit, which compares driver required torque with motor discharge restricting torque to determine the start of full load mode, thereby accurately controlling engine output.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If the engine part load maximum output torque is calculated using conventional methods without learning torque deviation, then the calculation is simple and fast, but the accuracy of torque calculation deteriorates due to discrepancies between HCU and EMS

Engineering Contradiction:

Improvetorque calculation accuracyVSAvoidcontrol system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system performs preliminary learning of torque deviation during normal operation before full load mode transition. The learning unit accumulates torque deviation data during part load operation, establishing a baseline correction value that is stored and applied when full load mode is needed, ensuring accurate torque calculation at the moment of transition.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The learning unit continuously monitors the difference between HCU-commanded torque and EMS-calculated torque during part load operation. This feedback mechanism captures the actual deviation between the two control systems, allowing the system to learn and compensate for discrepancies, thereby improving future torque calculation accuracy.

Inventive Principle:

Principle #23Feedback

2Productivity

If the hybrid control unit determines full load mode transition based on inaccurate engine output recognition, then the control response is fast, but fuel consumption increases due to premature or delayed mode switching

Engineering Contradiction:

Improvevehicle efficiencyVSAvoidmode transition timing accuracy

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system replaces direct mechanical torque sensing with an electronic learning-based torque estimation mechanism. By substituting physical measurement with intelligent algorithms that learn from operational data, the system achieves more accurate torque recognition that accounts for system-specific variations between HCU and EMS.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system dynamically adjusts the torque calculation parameters by incorporating learned deviation values. The torque deviation learning unit modifies the base torque calculation with correction factors derived from actual operational differences, allowing the system to adapt to changing conditions and maintain accuracy across different operating scenarios.

Inventive Principle:

Principle #35Parameter changes

3Force

If the air fuel ratio is controlled to be rich by increasing fuel amount to achieve torque greater than engine part load maximum output torque, then the required torque is achieved, but fuel consumption rapidly increases

Engineering Contradiction:

Improveengine torque outputVSAvoidfuel consumption

Core Design Contradiction:

ForceVSUse of energy by moving object

Solution Approach 1:

Instead of immediately switching to full load mode with rich air-fuel ratio when torque demand exceeds part load maximum, the system applies partial correction using learned torque deviation. This allows the HCU to more accurately determine the true part load maximum torque, delaying unnecessary full load transitions and avoiding excessive fuel consumption while still meeting torque requirements.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS10576960B2Apparatus and method for calculating maximum output torque of engine of hybrid electric vehicle

Publication Date: 2020.03.03 HYUNDAI MOTOR CO LTD

AI summary

An apparatus for calculating a maximum output torque of an engine of a hybrid electric vehicle includes a torque deviation calculating unit configured to calculate a torque deviation by using a currently output engine torque and an engine command torque, an engine output change learning unit configured to learn the torque deviation when a torque deviation learning start condition of the hybrid electric vehicle is satisfied, and an engine part load maximum torque calculating unit configured to calculate an engine part load maximum output torque based on the learned torque deviation so as to control an output of the engine.