Methods of estimating a weight of a vehicle and using the information are provided. Kinematic data of the vehicle, including at least one of a velocity or an acceleration of the vehicle, can be measured at a time. This data can be processed to estimate a weight of the vehicle. This data can be used to adjust autonomous driving, confirm a weight of freight carried by the vehicle, transmitted to external devices, or used in other ways.

Apparatuses, methods, systems and controls including dynamic vehicle parameter determination are disclosed. One embodiment is a method of operating a vehicle system including a powertrain comprising a prime mover structured to propel the vehicle, and an electronic control system in operative communication with the prime mover and the transmission. The method includes estimating a plurality of coefficients of a vehicle loss model, evaluating a convergence criterion for the plurality of estimated coefficients, setting converged values of the plurality of coefficients if the convergence criterion is satisfied, determining a vehicle powertrain command utilizing the converged values of the plurality of coefficients, and transmitting a vehicle powertrain command to control operation of one or more powertrain components.

In one embodiment, when speed control command (e.g., throttle, brake commands) is issued based on a target speed, a first feedback parameters is determined based on an expected speed and an actual speed of the ADV in response to the speed control command. A second feedback parameter is determined by applying a speed control parameter adjustment (SCPA) model to a set of input parameters that are captured or measured at the point in time. The set of input parameters represents a driving environment of the ADV at the point in time. One or more control parameters of a speed controller of the ADV is adjusted based on the first feedback parameter and the second feedback parameter, where the speed controller is configured to generate and issue speed control commands. Subsequent speed control commands can be generated based on the adjusted speed control parameters of the speed controller.

A hybrid vehicle comprises an engine, an energy storage device, and an aftertreatment system comprising a SCR catalyst configured to treat constituents of an exhaust gas. A controller is operatively coupled to the engine, the energy storage device, and the after treatment system, and configured to estimate an exhaust gas temperature and flow rate of the exhaust gas based on a set of engine operating parameters. The controller determines an exhaust gas cooling rate based on the exhaust gas temperature, flow rate, and a SCR catalyst temperature, and an ambient cooling rate based on an ambient temperature, a vehicle speed and the catalyst temperature. The controller determines a SCR catalyst temperature change rate based on the exhaust gas and ambient cooling rates, and adjusts a load distribution between the engine and the energy storage device based on the SCR catalyst temperature change rate.

A fuel control system obtains a measured amount of fuel consumed by an engine and one or more corresponding operating parameters of the engine and determines a fuel consumption modeled amount based at least in part on a fuel consumption model of the engine and the one or more operating parameters. The fuel consumption model associates different amounts of fuel that, when supplied to the engine, generate corresponding designated outputs of the engine. The system also determines one or more differentials between the measured amount of fuel and the modeled amount and, responsive to the one or more of the differentials exceeding a threshold value, the system identifies one or more components of the powered system that contribute or cause the one or more differentials and/or changes an amount of fuel supplied to the engine according to the fuel consumption model to obtain a desired output of the engine.

The present invention relates to a universal powertrain for controlling an effort request and/or a flow request to a powertrain based on a demanded effort or demanded flow for the powertrain. The universal controller includes a configurable powertrain model and a configurable optimiser module. The universal controller is configurable to control a class of generic powertrains comprising J generic power sources, K generic power sinks, and L generic couplings. The universal controller is arranged to receive an input file of a plurality of input parameters to configure the universal controller to control a specific powertrain having a powertrain architecture with N power sources, M power sinks, and X couplings, the configurable powertrain model comprising: (a) a generic powertrain component library configured to provide a model of each of the N power sources, M power sinks and X couplings of the specific powertrain, and (b) a connection parameter module configured to define a model architecture of the N power source models, M power sink models and X coupling models which is representative of the powertrain architecture based on flow weight parameters and effort weight parameters of the input file, the configurable optimiser module comprising: a generic performance objective function library comprising a plurality of configurable performance objective functions from which a cost function is configurable based on input parameters of the input file, wherein the configurable optimiser module is configurable to calculate at least one of an optimised effort request or an optimised flow request for each of the N power sources of the specific powertrain based on: the cost function, the powertrain model of the specific powertrain, the demanded effort request of demanded flow request.

A system and method for compensation of turbo lag in hybrid vehicles is disclosed. The system identifies a zero boost power limit of the engine and a torque curve power limit. A turbocharger dynamic model is then developed based on measurements of the input engine power and the output max available engine power. The model is used to determine an overall propulsion power limit based on the combination of the engine and motor in operation. A power request by the driver may then be limited to the overall propulsion power limit to compensate for the effect of the turbocharger when propelling the vehicle using both the engine and motor and better simulate the engine-only response.

A system and method for compensation of turbo lag in hybrid vehicles is disclosed. The system identifies a zero boost power limit of the engine and a torque curve power limit. A turbocharger dynamic model is then developed based on measurements of the input engine power and the output max available engine power. The model is used to determine an overall propulsion power limit based on the combination of the engine and motor in operation. A power request by the driver may then be limited to the overall propulsion power limit to compensate for the effect of the turbocharger when propelling the vehicle using both the engine and motor and better simulate the engine-only response.

Apparatuses, methods, systems and controls including dynamic vehicle parameter determination are disclosed. One embodiment is a method of operating a vehicle system including a powertrain comprising a prime mover structured to propel the vehicle, and an electronic control system in operative communication with the prime mover and the transmission. The method includes estimating a plurality of coefficients of a vehicle loss model, evaluating a convergence criterion for the plurality of estimated coefficients, setting converged values of the plurality of coefficients if the convergence criterion is satisfied, determining a vehicle powertrain command utilizing the converged values of the plurality of coefficients, and transmitting a vehicle powertrain command to control operation of one or more powertrain components.

To keep plant performance constant in a control apparatus for controlling a plant including a plurality of units. The control apparatus (a PCM) controls an automobile including a plurality of units. The control apparatus includes a model controller that generates a target value of a characteristic to be achieved by each unit based on a model set for each unit, a unit specifier (a performance change determinator) that specifies a unit in which performance unique to the unit has changed among the units, and a target value corrector (an FF updater) that corrects the target value for the unit that has been specified by the unit specifier.