Automotive Software Solutions  |  Powertrain Control  | System Architecture 
OnRAMP Design and Calibration Suites (OnRAMP) are an innovative model predictive control toolsets for advanced powertrain control and virtual sensing development.

OnRAMP Architecture Large
OnRAMP offerings available are:

• Diesel and Gasoline Airpath Solutions
• Thermal Management
• External Model Integration (AMESim or Simulink)
• Virtual Sensing (Turbo Speed Sensor, NOx, EGR /MAF)

• After-Treatment
• Predictive Cruise Control
• Battery Management
• Hybrid Powertrain Solutions
• Cycle Optimizer
• Waste Heat Recovery
• Transmission Control
OnRAMP leverages Honeywell’s expertise in advanced control to offer:

     • Plant modeling accomplished by specifying the basic engine layout from a component library then automatically fitting over the entire operating space of the engine
     • Multivariable model predictive controllers respecting engine constraints while being robust to model uncertainty due to production variability and engine ageing
     • Controllers designed to fit into a low memory footprint
     • ECU code whose structure does not change when the control is reconfigured for different engines.

OnRAMP Design and Calibration Suites are divided into a series of phases:

1. Model Design and Model Configuration
The user creates a physics-based engine model in Simulink by selecting predefined components from the library.

2. Design of Experiment and Model Identification
The model parameters are identified from plant data. Design of experiment data is generated by the tool. It covers both steady-state and transient modes. A simple process supports model parameter identification in three stages:

        1. Components identification
        2. Steady-state identification
        3. Transient identification

3. Control Problem Specification
The user creates a physics-based engine model in Simulink by selecting predefined components from the library.

4. Controller Design and Simulation
The controller includes both feedforward and feedback parts. The feedforward term is derived based on an inversion of the nonlinear model. The local linear dynamic models are used to design the multivariable’s feedback controller. The controller is then simulated against the identified nonlinear model.

5. Controller Deployment
The controller can be deployed as either MISRA compliant C-code or as a Simulink S-function. The handwritten C-code remains the same for all controller configurations – all that changes is the parameterized data.

6. Controller Implementation (RPS or ECU)

Both rapid prototyping system and direct implementation onto the ECU are supported.

7. Controller Tuning
Controller tuning on the target platform is supported for on-engine or in-vehicle operation.

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