Abstract: An engine and one or more aftertreatment subsystems integrated into one system for optimization and control. At least one controller may be connected to the engine and the one or more aftertreatment subsystems. The controller may contain and execute a program for the optimization and control of the one system. Controller may receive information pertinent to the engine and the one or more aftertreatment subsystems for the program. The controller may prescribe setpoints and constraints for measured variables and positions of actuators according to the program to aid in effecting the optimization and control of the one system.

Abstract: A system and approach for catalyst model parameter identification with modeling accomplished by an identification procedure that may incorporate a catalyst parameter identification procedure which may include determination of parameters for a catalyst device, specification of values for parameters and component level identification. Component level identification may be of a thermal model, adsorption and desorption, and chemistry. There may then be system level identification to get a final estimate of catalyst parameters.

Abstract: A system that provides an estimation of quantities, which are not necessarily directly measurable in a subsystem. The estimates of these quantities may be inferred from other variables. This approach may be referred to as inferential sensing. Physical sensors may be replaced with models or virtual sensors, also known as inferential sensors. The present approach may be a framework for designing inferential sensors in automotive subsystems. The framework may incorporate preparing a model for an observed subsystem, populating a real-time template with data, and running an inferential sensor periodically together with a model in real-time to obtain estimated variables. Once implemented, the framework may be reused for virtually any automotive subsystem without needing significant software code changes.

Abstract: A system and approach for catalyst model parameter identification with modeling accomplished by an identification procedure that may incorporate a catalyst parameter identification procedure which may include determination of parameters for a catalyst device, specification of values for parameters and component level identification. Component level identification may be of a thermal model, adsorption and desorption, and chemistry. There may then be system level identification to get a final estimate of catalyst parameters.

Abstract: An approach and system for robust constraints handling for measured disturbances with uncertain preview on a prediction horizon in model predictive control with application in automotive control systems A constraints handling system may incorporate a mechanism for measuring disturbances of automotive control subsystems, a model predictive controller that provides model predictive control, connected to the a mechanism for measuring disturbances, and a sensor subsystem that collects information about an uncertainty of measured disturbances. The disturbances may have an uncertain preview over a prediction horizon. Estimates for the disturbances may be made of the preview.

Abstract: An engine and one or more aftertreatment subsystems integrated into one system for optimization and control. At least one controller may be connected to the engine and the one or more aftertreatment subsystems. The controller may contain and execute a program for the optimization and control of the one system. Controller may receive information pertinent to the engine and the one or more aftertreatment subsystems for the program. The controller may prescribe setpoints and constraints for measured variables and positions of actuators according to the program to aid in effecting the optimization and control of the one system.

Abstract: A system for reducing environmentally harmful emissions from an internal combustion engine. The system may incorporate an exhaust after-treatment device. The exhaust after-treatment device may use selective catalytic reduction to remove certain emissions from the exhaust of the engine. Urea solution may be inserted into the exhaust emissions, which is decomposed to ammonia to become a reduction agent for reduction of NOx in the emissions. The engine may be managed by a controller and the exhaust after-treatment device may be managed by another controller. These controllers may be cascaded, or be managed by a third controller that provides hierarchical or coordinated control of engine performance and emissions reduction. The engine and the exhaust after-treatment device may be modeled to aid in designing and building a system for coordinated control of an actual engine and a selective catalytic reduction after-treatment device. The controllers may be predictive model controllers.

Abstract: Methods and systems are presented for improving performance of a vehicle operating in a cruise control mode where a controller adjusts torque output from a vehicle to maintain vehicle speed within a desired range while preventing the unnecessary downshifts. The methods and systems include adapting a vehicle dynamics model and a vehicle fuel consumption model that provide input to nonlinear model predictive controller.

Abstract: Methods and systems are presented for improving performance of a vehicle operating in a cruise control mode where a controller adjusts torque output from a vehicle to maintain vehicle speed within a desired range. The methods and systems include adapting a vehicle dynamics model and a vehicle fuel consumption model that provide input to nonlinear model predictive controller.

Abstract: A system for reducing environmentally harmful emissions from an internal combustion engine. The system may incorporate an exhaust after-treatment device. The exhaust after-treatment device may use selective catalytic reduction to remove certain emissions from the exhaust of the engine. Urea solution may be inserted into the exhaust emissions, which is decomposed to ammonia to become a reduction agent for reduction of NOx in the emissions. The engine may be managed by a controller and the exhaust after-treatment device may be managed by another controller. These controllers may be cascaded, or be managed by a third controller that provides hierarchical or coordinated control of engine performance and emissions reduction. The engine and the exhaust after-treatment device may be modeled to aid in designing and building a system for coordinated control of an actual engine and a selective catalytic reduction after-treatment device. The controllers may be predictive model controllers.

Abstract: A system for reducing environmentally harmful emissions from an internal combustion engine. The system may incorporate an exhaust after-treatment device. The exhaust after-treatment device may use selective catalytic reduction to remove certain emissions from the exhaust of the engine. Urea solution may be inserted into the exhaust emissions, which is decomposed to ammonia to become a reduction agent for reduction of NOx in the emissions. The engine may be managed by a controller and the exhaust after-treatment device may be managed by another controller. These controllers may be cascaded, or be managed by a third controller that provides hierarchical or coordinated control of engine performance and emissions reduction. The engine and the exhaust after-treatment device may be modeled to aid in designing and building a system for coordinated control of an actual engine and a selective catalytic reduction after-treatment device. The controllers may be predictive model controllers.

Abstract: An approach and system for engine and aftertreatment system optimization. Emissions of an engine may be reduced by an aftertreatment mechanism. Control of the engine and the aftertreatment mechanism may be coordinated for the best overall efficiency relative to both fuel consumption and the emissions reduction. Engine and aftertreatment control may also be optimized in terms of cost function minimization. Individual efficiencies of the engine and aftertreatment mechanism are not necessarily significant by themselves. Therefore, the engine and aftertreatment mechanism should be controlled in a manner to achieve the optimality of the engine and the aftertreatment mechanism together as one entity.

Abstract: Methods and systems are presented for improving performance of a vehicle operating in a cruise control mode where a controller adjusts torque output from a vehicle to maintain vehicle speed within a desired range while preventing the unnecessary downshifts. The methods and systems include adapting a vehicle dynamics model and a vehicle fuel consumption model that provide input to nonlinear model predictive controller.

Abstract: Methods and systems are presented for improving performance of a vehicle operating in a cruise control mode where a controller adjusts torque output from a vehicle to maintain vehicle speed within a desired range. The methods and systems include adapting a vehicle dynamics model and a vehicle fuel consumption model that provide input to nonlinear model predictive controller.

Abstract: A system and approach for catalyst model parameter identification with modeling accomplished by an identification procedure that may incorporate a catalyst parameter identification procedure which may include determination of parameters for a catalyst device, specification of values for parameters and component level identification. Component level identification may be of a thermal model, adsorption and desorption, and chemistry. There may then be system level identification to get a final estimate of catalyst parameters.

Abstract: An approach and system for robust constraints handling for measured disturbances with uncertain preview on a prediction horizon in model predictive control with application in automotive control systems A constraints handling system may incorporate a mechanism for measuring disturbances of automotive control subsystems, a model predictive controller that provides model predictive control, connected to the a mechanism for measuring disturbances, and a sensor subsystem that collects information about an uncertainty of measured disturbances. The disturbances may have an uncertain preview over a prediction horizon. Estimates for the disturbances may be made of the preview.

Abstract: A system that provides an estimation of quantities, which are not necessarily directly measurable in a subsystem. The estimates of these quantities may be inferred from other variables. This approach may be referred to as inferential sensing. Physical sensors may be replaced with models or virtual sensors, also known as inferential sensors. The present approach may be a framework for designing inferential sensors in automotive subsystems. The framework may incorporate preparing a model for an observed subsystem, populating a real-time template with data, and running an inferential sensor periodically together with a model in real-time to obtain estimated variables. Once implemented, the framework may be reused for virtually any automotive subsystem without needing significant software code changes.

Abstract: A system and method for solving a quadratic programming optimization problem with bound constraints using a semi-explicit QP solver with respect to an embedded platform is presented. A linear system of equations associated with a matrix (e.g., a Karush-Kuhn-Tucker matrix, KKT system) can be solved at each iteration of the solver based on a factorization approach. A set of partial factors with respect to the QP problem can be pre-computed off-line and stored into a memory. The factorization process of the KKT matrix can then be finished on-line in each iteration of the semi-explicit QP solver in order to effectively solve the QP optimization problems. The QP problem can be solved utilizing a standard active-set approach and/or a partial explicit approach based on a processor utilization and memory usage.

Abstract: A method and system of predictive model control of a controlled system with one or more physical components using a model predictive control (MPC) model, determining an iterative, finite horizon optimization of a system model of the controlled system, in order to generate a manipulated value trajectory as part of a control process. At time t sampling a current state of the controlled system a cost function minimizing manipulated variables trajectories is computed with the MPC model for a relatively short time horizon in the future, wherein the MPC uses a quadratic programming (QP) algorithm to find the optimal solution, and wherein the QP algorithm is solved using an Active Sets solver (AS) class algorithm with simple constraints based on gradient projection and using Newton step projection. A move of the manipulated value trajectory is implemented and the control process is moved forward by continuing to shift the prediction horizon forward.

Abstract: Methods and systems for the design and implementation of optimal multivariable MPC controllers for fast-sampling constrained dynamic systems utilizing a primal-dual feasibility approach and/or a graph approach. The primal-dual feasibility approach can compute and store matrices defining constraints of quadratic programming problems in an off-line part in order to calculate vectors of Lagrange multipliers and an optimizer. Then primal-dual feasibility can be checked in an on-line part using the Lagrange multipliers and the optimizer can provide a unique optimal solution for the constrained dynamic system. The graph approach can compute and store the matrices and the vectors, and also prepare and store a structure of directed graph in off-line part. An optimizer for a given parameter vector can be determined in on-line part using the directed graph, the matrices and the vectors.