Hybrid Vehicle Power Supply Control Using Historical Route Data

Solution Overview

Problem

Existing methods for optimizing energy consumption in hybrid transport vehicles, which have multiple energy sources, are not suitable as they do not adapt to repetitive routes and do not effectively utilize historical data from previous journeys to optimize energy use.

Innovation Solution

An electronic control device that processes historical data to estimate and manage the power requirements of an electric motor by distributing energy between a main and secondary source based on route profiles and external conditions, using a knowledge base and calculation units to optimize energy distribution and source usage.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If determined optimization functions are used for energy management, then energy optimization is achieved, but the system cannot adapt to repetitive routes and historical data is not utilized

Engineering Contradiction:

Improveadaptability to repetitive routesVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by storing historical journey data and route characteristics in advance. The knowledge base accumulates information from previous trips along the same route, enabling the system to predict future energy requirements based on pre-collected data about repetitive routes, weather conditions, and operational patterns.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms by continuously comparing actual energy consumption with predicted consumption from historical data. The knowledge base is updated with new journey information, allowing the optimization functions to learn from and adapt to repetitive routes over time, improving energy management decisions for future trips.

Inventive Principle:

Principle #23Feedback

2Productivity

If real-time optimization is performed without historical data, then immediate energy management is achieved, but optimization is not improved by learning from previous journeys

Engineering Contradiction:

Improveenergy optimization efficiencyVSAvoidloss of historical data utility

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The system performs preliminary actions by storing historical journey data and route characteristics in advance. The knowledge base accumulates information from previous trips along the same route, enabling the system to predict future energy requirements based on pre-collected data about repetitive routes, weather conditions, and operational patterns.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms by continuously comparing actual energy consumption with predicted consumption from historical data. The knowledge base is updated with new journey information, allowing the optimization functions to learn from and adapt to repetitive routes over time, improving energy management decisions for future trips.

Inventive Principle:

Principle #23Feedback

3Use of energy by moving object

If multiple energy sources are used without optimized distribution, then power supply flexibility is achieved, but energy consumption is not minimized

Engineering Contradiction:

Improveenergy consumptionVSAvoidenergy management complexity

Core Design Contradiction:

Use of energy by moving objectVSDevice complexity

Solution Approach 1:

The system segments the energy supply function by distinguishing between a main energy source and a secondary energy source. The control device separately manages each source based on specific criteria: the main source handles sustained power requirements while the secondary source provides peak power supplementation and stores regenerative braking energy, optimizing the overall energy consumption of the hybrid vehicle.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system dynamically changes operational parameters by adjusting the power distribution ratio between the main and secondary energy sources based on real-time conditions such as vehicle speed, acceleration demands, route characteristics from historical data, and battery state of charge. This parameter optimization minimizes total energy consumption while maintaining required performance.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentEP3162612B1Method for controlling the supply of a transport vehicle engine and associated device

Publication Date: 2018.07.04 ALSTOM TRANSPORT TECH SAS

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AI summary

The present invention relates to a method for controlling the power supply of an electric motor (12) of a vehicle, the vehicle comprising a main source (14) and a secondary source (16) for powering the motor (12), the secondary source (16) comprising a storage element. The process includes the following steps (100): - estimation (110) of a necessary electrical power (P(t)), - determination (112) of a frequency spectrum of the estimated power (P(t)), - calculation (114) of a first and second quantity (Q1(t), Q2(t)) of energy for supplying the motor (12), the calculation being carried out from the determined spectrum, the first quantity (Q1(t)) being supplied by the main source (14) and the second quantity (Q2(t)) being supplied by the secondary source (16), and - control (116) of the main source (14) and the secondary source (16) as a function of the first and second quantities (Q1(t), Q2(t)) calculated.