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Find out more about the latest release of AVL CRUISE M

AVL CRUISE™ M is a simulation solution that is tailored for system engineers in powertrain and vehicle development departments. It delivers functional flexibility based on its modular structure, which provides the freedom to explore and develop all possible designs. Its unique real-time capability empowers model-based calibration, proven as part of AVL’s calibration toolchain.

And now we have updated this powerful tool. The latest release, CRUISE M 2019 R2, enters the market with a range of improvements to bring even more value to your simulation toolchain.

New Double Clutch Transmission (DCT) Component

We have extended the CRUISE M Driveline component library with a new Double Clutch Transmission (DCT) component. This is ideal for many use cases where a detailed gearbox assembly modeled out of basic components for each gear ratio is not needed. As such, a dedicated DCT component eases up and significantly shortens the setup of the powertrain configuration.

Beside regular parameterization options the component includes two features to describe transmission losses and the choice of a built-in thermal model. Transmission losses can be provided as gear dependent efficiencies and as torque losses depending on gear, speed, torque and temperature. The thermal model features three different modeling depths. These are fixed temperature (changeable via data bus), variable temperature with an explicit connection to the cooling networks, and variable temperature with simplified loss model.

Double Clutch Transmission setup

New Double Clutch Transmission Control Component

A new DCT (Double Clutch Transmission) Control component is introduced simultaneously with a DCT gearbox component featuring functionalities needed to control it. At any point, the user can substitute it with his own DCT Control applying his own control strategy.

DCT Control serves as a central manager of all the control activity for clutch actuation. During the gear shifting process, it takes the torque input as the leading control variable.

The clutch actuation at launch features three options:

  • The clutch release is simply determined with launch speed
  • It can be defined as a function of load, level of launch speed and speed tolerance window
  • It is exposed to the data bus network to be freely defined by external controller

The clutch actuation at stop conditions features the same input options as for launch conditions. In addition, the “use actuation at launch map” option will shorten the parameterization, skipping the repeated input of data sets.

The shifting process definition table contains torque and speed phase times. This influences clutch actuation at gear change, from active to ongoing gear for different torque levels taking into account engine side inertia. The DCT gearbox component provides the speed synchronization time, as it depends on the synchronizer mechanics. The user can substitute the integrated pre-selection strategy. This is done with a user-defined one via the signal coming from the data bus.

New Cycle Run and Full Load Acceleration Driving Tasks

This latest release enables a faster and more efficient setup of simulation tasks related to the vehicle attributes assessment. Additionally, it supports the investigation of impact with respect to factors such as different vehicle configuration concepts, components sizes and control strategies. The update to CRUISE M offers two new dedicated driving tasks components. The Cycle Run task answers the questions related to fuel consumption while the Full Load Acceleration task provides feedback about the vehicle performance.

Both of these task components combine the functions of the driver, environment, and profile in a compact manner. This is focused on task-specific parameters to speed up the task definition setup. In this context, both components also feature a list of links to key plant model parameters, such as initial battery SOC, vehicle driving resistance, etc.

By using components such as driver, environment, and profile in combination with user-specific control components, users can still set up their own additional tasks. This is to answer other questions that are needed to reach their own development targets.

New dedicated Cycle Run and Full Load Acceleration driving tasks setup

Electro-chemical Model for PEM Fuel Cell

CRUISE M presents a new electro-chemical model for a PEM fuel cell stack. This is designed to support Balance of Plant (BoP) development activities, thermal layout optimization, media supply control development and transient response optimization. Furthermore, it supports real-time control function development and testing.

Additionally, it provides consistency between models featuring different complexity levels. This closes the gap between empirical PEM fuel cell system model, based on the polarization curve, and 3D electro-chemical CFD model in AVL FIRE™.

The new model describes the 3D behavior of a fuel cell used in AVL FIRE with a real-time hybrid analytical-numerical approach. This is where a representative pair of fuel cell channels is cut into discrete slices along the flow direction. It is here that the transport of mass, species and heat is calculated numerically.

The preprocessed analytic approach, featuring multi-component species diffusion, solves diffusive and advective species fluxes through the gas diffusion layers and membranes within each slice. Similarly, electrical potential field and current fluxes are solved analytically. The Butler-Volmer equation models the reaction of oxygen reduction in the catalytic layer.

The transport of the produced liquid H2O through the gas diffusion layers is modeled in analogy to gaseous species transport. Outside the membrane, water is transported as gaseous, for now. The concentration of liquid water is extracted from the levels of supersaturation.

The new electro-chemical PEM FC component is integrated into the gas flow, electrical and thermal network in an open manner following the FMI standard. This enables high flexibility in adapting the FC component to requirements from the surrounding BoP systems.

The model is validated with a series of experimental validations of which some are published in literature by several scientific papers. It is additionally compared to results from the FIRE 3D FC model and ensure the highest possible consistency. This enables a seamless workflow between CFD simulations and system level simulation in CRUISE M.

Electro-chemical PEM Fuel Cell model parameterizationp

Spark Ignited Combustion

This version of CRUISE M introduces a new combustion model for a spark ignited engine. The AVL Spark Ignited Combustion model is a real-time capable, quasi-dimensional model that predicts the rate of heat release in homogeneous charge engines. The model includes combustion chamber geometry parameterization, spark plug position, spark timing, and state (pressure, temperature). Additionally, the composition of the cylinder charge (air, residual gas content and fuel vapor) and the macroscopic charge motion and turbulence level are also modeled.

Furthermore, it employs the concept of modeling the evolution of the flame surface in a homogeneous charge. The flame surface evolution is governed by the turbulent flame front velocity, which is driven by the laminar flame speed and the turbulence level. It is assumed that the flame progresses in a spherical shape that intersects with the combustion chamber walls. The actual flame surface is pre-calculated for standard cylinder geometries and is imported from a file.

The application of the model showed two input parameters (ignition timing and flame speed multiplier over speed and load) achieve reasonable correlations with experimental data. For experienced users, additional input on flame speed and turbulence are offered as an option. The AVL Spark Ignited Combustion model can be combined with the other existing models such as knock and water injection models.

Simulation vs. measurement for BMEP and MFB50

Waste Heat Recovery

CRUISE M offers a new modeling domain which supports the simulation of waste heat recovery systems. The functionality is based on the solver framework for arbitrary Vapor-Liquid Equilibrium (VLE) circuits combined with a media library of all relevant refrigerants.

To describe waste heat recovery systems, the existing component library (pipes, valves, compressors, boundary conditions, heat exchangers, junction, etc.) is extended with three new components. These are:

  • The “Simple Expander” component. This can be used as a starting point as it requires only little inputs (i.e. constant or variable flow rates) and at defined downstream temperature.
  • The “Efficiency Expander” component. This expands a two-phase flow depending on its rotational speed, the actual displacement, and three user-defined efficiencies.
  • The “Second Order Pump” component. This calculates the pressure increase depending on the rotational speed by using affinity laws. The actual speed of the pump model can either be a fixed value or given externally via mechanical connection. The calculation of the pressure difference is based upon a quadratic correlation between pressure increase and volumetric flow.

Organic rankine cycle for Energy Management Simulation

Thermal Reduced-Order Model and Parameterization Wizard

CRUISE M presents new modeling capabilities to describe the transient thermal behavior of solid structures in a numerically highly efficient manner. This is based on the solution of linear time-invariant (LTI) thermal problems. To use LTIs, real physical problems must have constant material properties and linear boundary conditions.

Where this is the case, it is easy to characterize the physical problem with a step impulse and the following step response. This could be a heat pulse followed by a temperature response, for example. To describe such step-responses, we establish so-called Foster networks (cascaded RC pairs) that use parameters fitting the R and C values. The reference data used in the fitting process typically originate from measurements or high-resolution CFD simulations. CRUISE M supports the application of LTIs with a new component – “Thermal ROM” (Thermal Reduced Order Model) – which includes a dedicated parameterization wizard.

The wizard takes inputs for an arbitrary number of heat sources. The user can configure the number of output temperatures, number of RC pairs and variable coolant temperatures. Using regression methods, it calculates all RC parameters to best match the given reference data. The wizard then automatically transfers the obtained RC values to the corresponding Thermal ROM component. The ROM component features data bus inputs to link to proper heat sources and to return the calculated temperatures.

When using thermal ROMs for thermal battery modeling, the user can couple them to an electrical battery model to achieve a complete electro-thermal battery simulation. The electro-thermal model can be utilized either as a physical model of a battery system or used for battery thermal management system in the battery controller.

Parameterization Wizard for Thermal ROM