Hybrid Drivetrain State Selection via Cumulative Filtering
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Solution Overview
Problem
Existing methods for selecting the state setpoint of a hybrid vehicle's kinematic chain fail to simultaneously optimize consumption, pollution control, driving pleasure, and acoustics due to the complexity of managing energy modes and power distribution between internal combustion engines and electric motors.
Innovation Solution
A method involving a sequence of filtering steps to determine eligible kinematic chain states based on cumulative approval constraints, including initialization of eligibility vectors, Human Machine Interface considerations, speed and mechanical constraints, and force constraints, ensuring optimal energy management and state selection for hybrid powertrains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a conventional transmission state selection method is used, then the structure is simple, but it cannot manage multiple energy modes and power distribution in hybrid powertrains
Solution Approach 1:
The patent segments the hybrid powertrain operation into distinct energy modes (electric-only, hybrid, charge sustain, charge depleting) and defines specific drivetrain states for each mode. This segmentation allows the system to manage complexity by treating each mode separately with mode-appropriate state definitions, rather than attempting to handle all possibilities in a single unified approach.
Solution Approach 2:
The patent implements dynamic adaptation of the drivetrain state definition based on the current energy mode. The set of available drivetrain states changes dynamically depending on whether the vehicle is in electric-only mode, hybrid mode, charge sustain mode, or charge depleting mode. This dynamic approach allows the system to simplify state selection when possible while maintaining full capability when needed.
2Adaptability or versatility
If multiple drivetrain states are defined for hybrid powertrains, then energy mode management capability is improved, but the number of states and selection complexity increases
Solution Approach 1:
The patent divides the drivetrain states into mode-specific subsets. Each energy mode has its own defined set of valid drivetrain states, which are determined based on the current operating conditions and mode requirements. This segmentation reduces the effective number of states that need to be considered at any given time, making selection more manageable.
Solution Approach 2:
The patent performs preliminary determination of the energy mode before proceeding to drivetrain state selection. By first establishing which energy mode is active (electric-only, hybrid, charge sustain, or charge depleting), the system pre-filters the available drivetrain states to only those appropriate for the current mode, reducing the search space and simplifying the subsequent state selection process.
3Use of energy by moving object
If drivetrain state selection optimizes fuel consumption, then energy efficiency is improved, but other constraints like acoustics and driving pleasure may be compromised
Solution Approach 1:
The patent implements a dynamic multi-objective optimization approach where the drivetrain state selection considers multiple competing objectives simultaneously. The system dynamically adjusts the weighting and priority of different objectives (fuel consumption, acoustics, driving pleasure, emissions) based on current operating conditions, driver preferences, and environmental factors. This allows the system to balance competing requirements rather than optimizing for a single parameter.
Solution Approach 2:
The patent changes the operational parameters of the drivetrain states based on multiple optimization criteria. Instead of selecting states based solely on fuel consumption, the system evaluates states based on a composite assessment that includes fuel efficiency, acoustic characteristics, driving pleasure metrics, and emissions. The selected state's parameters (torque distribution, gear selection, clutch engagement) are adjusted to achieve an optimal balance across all these parameters.
4Productivity
If the drivetrain state selection considers all constraints (consumption, pollution, acoustics, driving pleasure), then overall performance is optimized, but the selection process becomes more complex
Solution Approach 1:
The patent segments the constraint evaluation process into distinct modules, each handling a specific aspect (fuel consumption evaluation, emissions assessment, acoustic analysis, driving pleasure metrics). This modular segmentation allows each constraint to be evaluated independently using specialized algorithms, and then integrated into the overall decision-making process. The segmentation reduces complexity by breaking down the monolithic optimization problem into manageable sub-problems.
Solution Approach 2:
The patent introduces an intermediary energy mode determination step that mediates between the multiple constraints. By first determining the appropriate energy mode based on battery state of charge and operating conditions, the system creates an intermediate layer that filters and organizes the available drivetrain states before applying the full multi-objective optimization. This intermediary step simplifies the subsequent optimization by reducing the search space and providing a structured framework for evaluating multiple constraints.
Data Source
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AI summary
The invention relates to a method for selecting, among a set of states provided on a transmission, the target state of a vehicle drive train connecting at least one heat engine and/or an electric machine to the wheels of the vehicle via the transmission, wherein said states are defined by various combinations of the couplers and reducers of the transmission in order to ensure the transfer of the torque from the heat engine and/or from the electric machine to the wheels through one or more gear ratios. The method is characterised in that the selection of the target state complies with a sequence of filters determining, from a list of available states, groups of consecutive eligible states in accordance with cumulative approval constraints.