Powertrain Blockset™ provides a set of fully assembled reference applications, including gasoline (spark-ignition, SI), diesel (compression-ignition, CI), hybrid, and electric vehicle systems, as a starting point for your powertrain system model. To model a powertrain system for your project, you can select a reference application based on the powertrain type. Each reference application includes plant models, controllers, a longitudinal driver, and drive cycle data.
The reference applications come with a Simulink® Projects configuration. Simulink Projects enables management and version control for top-level model files, component model files, and scripts.
System Model Tailored to Your Project
Reference applications serve as a starting point for your system model. To tailor a reference application to your powertrain project, parameterize the components in the reference application using data from a domain-specific tool, a test bench, or a vehicle. Depending on your application and powertrain configuration, you might need to select the type of component models and further customize the system model.
The component library in Powertrain Blockset provides blocks of physical systems and controllers for:
All the models in Powertrain Blockset, including the reference applications and components in the library, are fully open for customization. You can use Simulink Projects to manage model variants including variant selection, version management, and comparison.
Mapped and Dynamic Combustion Engine Models
Powertrain Blockset provides two types of combustion engine models: mapped and dynamic. Mapped engines represent macro engine behavior as a set of lookup tables (brake torque, fuel flow, air mass flow, exhaust temperature, efficiency, and emissions) as functions of commanded load and measured engine speed. Dynamic engines decompose engine behavior into individual component models that account for engine dynamics, most notably intake airflow and turbocharger dynamics.
You can switch between engine model types based on your application. Dynamic engine models are suitable for designing control, estimator, and diagnostic algorithms that depend on dynamic subsystem states, for example, in closed-loop AFR control algorithm development. Mapped engine models are suitable for analysis and design activities that do not require engine subsystem dynamic characteristics, for example, in engine and transmission powertrain matching analysis for fuel economy, emissions, and performance tradeoffs.
Both the SI and CI engine models run in real time for hardware-in-the-loop (HIL) testing.
Electrified Powertrain Components
Powertrain Blockset includes reference applications for common electrified powertrains such as electric and multimode hybrid electric. These reference applications are open so you can configure and parameterize the electrified powertrain components, including motors, generators, and energy storage.
For system and control development, including HIL testing, these blocks provide a balance of realistic closed-loop behavior and simulation speed. You can customize your model to perform more detailed analyses. For example, you can include the effects of power electronics switching by using blocks from Simscape Power Systems™. You can also predict electrical efficiencies and losses using blocks from Simscape Electronics™.
Built-In Controller Models
Powertrain Blockset provides simple controller models for subsystems, including combustion engines, transmissions, and electric motors. These controller models serve two primary purposes.
First, the controller models complete a powertrain system model. This is important when, for example, you are testing the transmission controller’s interaction with other systems in a vehicle. By including an engine controller with the engine in the system model, you can reproduce the interaction between the transmission and engine during a shift event in simulation.
Second, the built-in controller models serve as a starting point for your controller development, so you do not need to build one from scratch. The controller models are based on common practices in the industry and employ the latest capabilities in Simulink®.
User-Defined Controller Models
The controller models within each reference application are designed in a modular and hierarchical manner. As you develop your own controllers, you can replace each component of the built-in controller. Using this method, you can use the reference application model as a virtual dynamometer or a virtual vehicle to test your controller step-by-step. You start with one feature at a time, and then group feature models into a more complete controller model for integration testing against the plant model
Embedded estimators are widely used in control design to eliminate a sensor or to implement a virtual sensor when a physical sensor cannot be used. The combustion engine controllers include state estimators for estimating torque, exhaust temperature, EGR flow, back-pressure, airflow, manifold pressure, AFR, and engine load. You can take advantage of these model components when developing your own estimator, reducing the initial design and architecting effort. Also, these estimators are identical to their corresponding subsystems inside the engine plant models. Consequently, once an engine plant model is parametrized, the parameter values can be automatically reused for the estimator. The estimator models are designed for ECU implementation using Embedded Coder®.
In addition to controller design and test, you can use the reference applications for powertrain design tradeoff studies, such as emissions, fuel economy, and performance. The mapped engine and motor blocks use data that is readily available from component suppliers, making them suitable for initial tradeoff analysis. To account for dynamic effects on the powertrain in fine-grained tradeoff studies, you can use the dynamic engine and motor blocks, for example, in studies that require the effect of turbocharger windup or electric motor control algorithms.
Design tradeoff studies often require tens of thousands of simulation runs. You can use MATLAB® to automate simulations and analyze the results. The advanced optimization functions in Optimization Toolbox™ can automatically find the best set of design parameters. To reduce the overall simulation time, you can use Parallel Computing Toolbox™ to deploy powertrain system simulations across a cluster of computer cores.
To support the needs of HIL testing, models must strike a balance between fidelity and simulation speed. The blocks in Powertrain Blockset provide the detail necessary to capture important physical effects (turbocharger windup, manifold filling and empty dynamics, driveline dynamics, etc.), while achieving high simulation performance and fast real-time execution. You can use both the dynamic and map-based engine models in reference applications for HIL testing. This gives you the freedom to start with a reference application, tailor the data to meet your needs, and then perform HIL testing on your controller model.
Modifying Existing Subsystems
Powertrain Blockset provides blocks for various automotive subsystems. However, you may want to customize one of the subsystems to capture specific dynamics of interest. The blocks are open and documented, so you can modify the libraries to suit your needs. For example, you can make a copy of the dynamic CI engine block from the library and add a throttle to capture the effects on air intake and exhaust dynamics. You can include the new CI engine block as an additional subsystem variant in the reference application, creating vehicle configurations with either the default engine or your customized version
Integration with Simscape
Reference applications in Powertrain Blockset enable you to test custom models for individual components by replacing the built-in subsystems with a variant of your own. For example, you can build a drivetrain model based on physical connections using Simscape Driveline™and Simscape Fluids™, then put it into a closed-loop vehicle model from Powertrain Blockset. Coupling custom designs with Powertrain Blockset in this way enables comprehensive testing at the system level. Reusing the framework of the reference application accelerates the setup and execution of subsystem tests while providing the flexibility to tailor the vehicle model to your specific needs.