Engine control unit calibration

A method of calibrating an ECU for an engine, the method comprising:

• for a plurality of iterations:
• determining, based on an objective function, a set of locations in an input space, each location in the input space representing a value of each of a plurality of variables,
• wherein the plurality of variables comprises:
• one or more context variables which, when engine is in use, have values derivable from driving system inputs and/or environmental inputs;
• and
• one or more decision variables representing parameters of the engine adjustable by the ECU in dependence on values of the one or more context variables,
• wherein the objective function is arranged to evaluate outputs of one or more Gaussian process models for a candidate set of locations, the one or more Gaussian process models each having a respective set of trainable parameters and being arranged to predict, for a given location in the input space, respective probability distributions for one or more of the plurality of engine performance characteristics,
• wherein the objective function is penalised in dependence on a likeliness predicted by the one or more Gaussian process models of one or more predetermined engine constraints being violated for a given location of the candidate set of locations;
• obtaining measurements of each of the plurality of engine performance characteristics covering at least a subset of the selected set of locations in the input space;
• and
• updating, using the obtained measurements of the plurality of engine performance characteristics, values for the respective set of trainable parameters of each of the one or more Gaussian process models;
• and
• generating, using probability distributions for the plurality of engine performance characteristics predicted by the one or more Gaussian process models, ECU calibration data for mapping values of the one or more context variables to values of the one or more decision variables.

One or more non-transitory storage media comprising instructions which, when the instructions are executed by a computer, cause the computer to carry out operations comprising:

• for a plurality of iterations:
• determining, based on an objective function, a set of locations in an input space, each location in the input space representing a value of each of a plurality of variables,
• wherein the plurality of variables comprises:
• one or more context variables which, when engine is in use, have values derivable from driving system inputs and/or environmental inputs;
• and
• one or more decision variables representing parameters of the engine adjustable by the ECU in dependence on values of the one or more context variables,
• wherein the objective function is arranged to evaluate outputs of one or more Gaussian process models for a candidate set of locations, the one or more Gaussian process models each having a respective set of trainable parameters and being arranged to predict, for a given location in the input space, respective probability distributions for one or more of the plurality of engine performance characteristics,
• wherein the objective function is penalised in dependence on a likeliness predicted by the one or more Gaussian process models of one or more predetermined engine constraints being violated for a given location of the candidate set of locations;
• obtaining measurements of each of the plurality of engine performance characteristics covering at least a subset of the selected set of locations in the input space;
• and
• updating, using the obtained measurements of the plurality of engine performance characteristics, values for the respective set of trainable parameters of each of the one or more Gaussian process models;
• and
• generating, using probability distributions for the plurality of engine performance characteristics predicted by the one or more Gaussian process models, ECU calibration data for mapping values of the one or more context variables to values of the one or more decision variables.