4.1.1.2. bca_tool_code.engine_input_modules package

4.1.1.2.1. Submodules

4.1.1.2.2. bca_tool_code.engine_input_modules.engine_learning_scalers module

INPUT FILE FORMAT

The file format consists of a one-row data header and subsequent data rows.

The data represent a “seed volume factor” that serves to slow learning effects; the higher the seed volume factor the slower the learning while a lower number results in more rapid learning.

File Type

comma-separated values (CSV)

Sample Data Columns

optionID	regClassName	regClassID	FuelName	fuelTypeID	SeedVolumeFactor	Notes
0	LHD	41	Gasoline	1	1
0	LHD	41	Diesel	2	10	SeedVolumeFactor: 10 to slow learning beyond first use
0	LHD	41	CNG	3	10	SeedVolumeFactor: 10 to slow learning beyond first use

Data Column Name and Description

optionID:

The option or alternative number.

regClassName:

The MOVES reg class name, a string.

regClassID:

The MOVES regClassID, an integer.

FuelName:

The MOVES fuel name, e.g., ‘Gasoline’, ‘Diesel’.

fuelTypeID:

The MOVES fuelTypeID, an integer.

SeedVolumeFactor:

The value of the seed volume factor, an integer.

Notes:

Notes pertinent to the data; Notes are ignored in code.

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CODE

class EngineLearningScalers

Bases: object

The EngineLearningScalers class reads the engine_learning_scalers input file and provides methods to query its contents.

__init__()

init_from_file(filepath)

Parameters:

filepath – Path to the specified file.

Returns:

Reads file at filepath; converts monetized values to analysis dollars (if applicable); creates a dictionary and other attributes specified in the class __init__.

get_seedvolume_factor(engine_id, option_id)

Parameters:

• engine_id – tuple; (regclass_id, fueltype_id).

• option_id – int; the option_id.

Returns:

The seed volume factor for the given engine and option_id.

calc_learning_effect(vehicle, sales_year1, cumulative_sales, learning_rate)

Parameters:

• vehicle – object; an object of the Vehicle class.

• sales_year1 – numeric; the sales in the first year of implementation of a new standard.

• cumulative_sales – numeric; the cumulative sales since and including the first year of implementation of a new standard.

• learning_rate – numeric; the learning rate set via the General Inputs file.

Returns:

The learning effect or factor to be applied to first year costs to reflect the learned cost after sales have totaled cumulative_sales.