AVL Simulation Suite R2026.1.1 Win x64

Software Overview

AVL Simulation Suite provides a connected environment for developing and analyzing powertrain and vehicle technologies. AVL CRUISE M supports multi-physical system simulation, AVL FIRE M focuses on computational fluid dynamics and detailed powertrain processes, AVL EXCITE M addresses structural dynamics and NVH-related applications, and AVL VSM provides vehicle-system simulation.
The suite also connects detailed component models with system-level and real-time simulation workflows. This allows engineers to investigate energy flows, thermal behavior, combustion, emissions, battery performance, fuel-cell and electrolyzer operation, vehicle dynamics, drivetrain vibration, lubrication, and related engineering parameters.
Additional capabilities in AVL Simulation Desktop, AVL IMPRESS M, AVL EXPLORE, and ChatSDT extend the environment with result visualization, optimization, data analysis, surrogate modeling, and AI-assisted interaction.

Key Features

• Multi-physical system simulation: Analyze energy transport and conversion across gas, liquid, electrical, and other physical domains.
  
• RF and powertrain development workflows: Support conventional, battery-electric, fuel-cell, electrolyzer, hybrid, and ICE-based development activities.
  
• Advanced battery simulation: Model heterogeneous LMFP/NMC electrodes, thermal runaway, venting gases, and temperature-dependent capacity.
  
• Fuel-cell and electrolyzer modeling: Simulate porous media, AEM and alkaline electrolyzers, SOFC/SOEC reaction zones, catalyst layers, and Knudsen diffusion.
  
• ICE simulation: Support in-cylinder flow, fuel injection, air-fuel mixing, ignition, combustion, and emissions analysis.
  
• Vehicle dynamics: Simulate off-road behavior, ride and comfort, tire-road interaction, braking, and tire temperature effects.
  
• CAD integration: Import native CAD data and automatically derive models for manifolds, bodies, and subcomponents.
  
• NVH and drivetrain analysis: Analyze engine mounts, gears, bearings, spline friction, cam-roller contacts, and other dynamic systems.
  
• Machine-learning integration: Import ONNX models into CRUISE M and use custom models through FMU and Simulink-based extensions.
  
• Optimization and DoE: Use conventional and adaptive Design of Experiments workflows for parameter studies, surrogate modeling, and optimization.
  
• Data analysis: Connect Simulation Desktop datasets and FMU-based models with AVL EXPLORE for analysis and sensitivity studies.
  
• AI-assisted support: Use ChatSDT to reference active models and selected elements through natural-language queries.
  

AVL CRUISE M

Vehicle Systems
Model Flow Diagram - Assessment of States and Fluxes
AVL CRUISE M extends Model Flow Diagrams with visual information about component states, port states, and energy or mass fluxes. Temperatures and other component states can be displayed through colored frames, port values such as speed can appear as labels, and quantities such as mass flow can be represented through connection lines with adjustable width.
AVL IMPRESS M provides configuration controls for MFD visualization, including colors, value ranges, units, and the visibility of domains, ports, connections, and frames.

Neural Network Evaluator - Import of ONNX
CRUISE M introduces a dedicated ONNX component for integrating data-driven models into physical system simulations. Instead of implementing a neural-network evaluator manually through a Compiled Function, users can load an ONNX file directly into the component.
Models trained with tools such as sklearn, PyTorch, MATLAB, TensorFlow, or other ONNX-compatible applications can be imported. CRUISE M determines the input and output channels from the model and connects them to the surrounding system model. During simulation, the imported model structure is interpreted and evaluated as part of the system simulation.

Battery Systems
Electrochemical Battery - LMFP Model
CRUISE M supports heterogeneous electrode modeling for lithium-ion batteries that use blends of electrode materials. The release demonstrates this approach with a commercial 26700 cylindrical cell using an LMFP/NMC blended cathode.
The heterogeneous model represents the two materials separately, while the homogenized approach represents them through one effective cathode material. Both approaches can be parameterized using experimental data. The heterogeneous treatment becomes particularly relevant at low temperatures and high loads, where LMFP diffusion and NMC kinetics affect capacity behavior differently. Material-dependent depth of discharge also helps represent temperature-related capacity reductions caused by diffusion limitations.

Battery Modules - Venting Gas Formation
CRUISE M extends battery thermal-runaway propagation modeling by accounting for venting gases. Battery Module and Discretized Solid 3D components use meshing-free 3D representations of configurable cell assemblies and cooling layouts for efficient thermal-runaway analysis.
The thermal-runaway and venting input page allows users to define venting-gas mass flow and temperature as functions of time or local solid and cell temperature.

Fuel Cell & Electrolyzer Systems
Fuel Cell and Electrolyzer Stack - Speedup
The PEM Fuel Cell, PEM Electrolyzer, and SOxC stack components support three-dimensional stack representations with configurable spatial resolution, gas-channel geometry, and flow direction.
The release adds non-uniform discretization along the stack height. Engineers can use finer resolution in areas such as the stack bottom where cooling or inflow conditions require additional detail, while using coarser resolution elsewhere. Since simulation time generally scales with the number of computational cells, this approach can reduce computational cost and provide speedups of up to one order of magnitude depending on the model and accuracy requirements.

Fuel Cell and Electrolyzer Wizards - Parameter Sensitivity
The parameterization wizards for PEM Fuel Cell and Electrolyzer Stack components can use the Fisher Information Matrix to assist with parameter selection. Users provide reference data and identify parameters for estimation, with sensitivity information available as an optional heat map.
Large diagonal values indicate parameters for which small changes produce significant response changes, while low values can indicate parameters that may be replaced with constants.

Thermodynamics & Exhaust Aftertreatment Systems
Head Block Component - Thermal Assessment in 3D
The new Head Block component provides a full 3D representation of temperature distribution in engine structures such as liners, heads, and valves. Instead of relying exclusively on 0D lumped-mass networks, users can generate a 3D head-block geometry from a limited set of geometric inputs and create a finite-element model with defined boundary conditions.
Flux boundaries can be connected to CRUISE M heat-transfer and cooling-flow networks. CRUISE M solves the FE model and returns three-dimensional results. For applications primarily concerned with input/output behavior, Model Order Reduction can provide a reported speedup of approximately 1000 while retaining the accuracy of the full FE model.

1D-3D Thermodynamic Simulation - Right-Sized Modeling Depth
CRUISE M and AVL FIRE M can combine one-dimensional gas-dynamic models with three-dimensional simulations in a single workflow. This is useful for effects that are difficult to represent accurately with purely 1D models, such as EGR distribution in intake manifolds or complex wave behavior in air boxes.
The workflow prepares the 1D and 3D models, defines interfaces, wraps the 3D model into an FMU, and loads that FMU into CRUISE M. New Gas Flow Interface and Gas Flow FMU components support the co-simulation setup. In addition to FMI-based coupling, isolated 1D and 3D simulation periods can be defined to stabilize the individual domains before full coupling.

CAD Import - Automated Creation of Manifold Models
CRUISE M extends its CAD Importer to support intake and exhaust manifold modeling. The workflow uses SHAPE to process CAD data, prepare inlet and outlet ports, and stage the manifold.
The analysis identifies pipe centerlines and junction branches and provides visual feedback within the CAD environment. After staging, the resulting pipe and junction network can be imported into CRUISE M as a subsystem ready to connect with a thermodynamic model.

AVL EXCITE M
CAD Import - Model Derivation from Native CAD Data
AVL EXCITE M can create bodies and subcomponents directly from common native CAD formats. Body coordinate systems, component positions, orientations, and parametric geometry can be derived from imported CAD data, reducing repetitive manual model definition.
An overlay of the CAD geometry and generated EXCITE M model allows users to verify alignment and imported information. The workflow supports complete-model creation as well as selective import of individual components.
EXCITE M also provides tools for simplifying, modifying, repairing, and measuring CAD geometry. Dimensions such as widths and diameters can be selected and updated directly from the CAD representation, helping maintain consistency when designs change.

Mount Layout Analysis Assembly
The Mount Layout Analysis Assembly provides a workflow for engine-mount layout definition, early NVH assessment, and design optimization using simplified rigid or flexible bodies. Mounts and torque brackets can be configured so that joints are inserted and connected automatically.
A global configuration menu contains the principal properties and settings, while multiple mount-joint types allow different mount concepts to be represented. Mount, body, and torque-bracket positions and orientations can be parameterized for optimization and DoE studies.
The analysis also visualizes the torque roll axis. Modal-analysis support includes rigid bodies in modal results and surface-mesh deflections for improved interpretation of dynamic behavior.

Consideration of Pitch Error for Cylindrical Gears
The inner and outer cylindrical gear subcomponents of the Advanced Cylindrical Gear joint support pitch-error definitions for representing manufacturing allowances. Three methods are available: single pitch deviation, cumulative pitch deviation, and harmonic functions.
Pitch error can be assigned independently to each flank side or applied as a common error to both sides. During simulation, the specified error is combined with defined microgeometry and misalignments such as tilting.


Stick-Slip Behaviour for Axial Friction in Spline Gear Joint
The axial friction model for spline-gear connections has been extended with an elasto-plastic representation to capture frictional locking between shafts and hubs. The elastic component represents the stick phase until the yield-friction limit is reached. Once external loading exceeds that limit, the model transitions into slip mode through the viscous part of the Bingham model.
This approach avoids the simplifications associated with a basic Coulomb model and does not require explicit regularization for the stick-to-slip transition. It is intended to represent friction locking in gearbox and electric-drive-unit applications in accordance with the underlying physical behavior.

Thrust Rolling Element Bearings
The new Thrust Roller Bearing joint provides dedicated axial-load modeling and introduces Needle Roller Thrust Bearing and Thrust Ball Bearing components. These models calculate axial stiffness, deflection, and load-carrying behavior for systems dominated by thrust forces.
They also account for time-varying stiffness caused by rolling-element over-rolling. Result quantities follow the output structure used for radial rolling-element bearings, providing consistent results across bearing types. The capability is applicable to drivetrain and powertrain systems such as planetary gear sets and electric drive units where helical-gear or rotor-dynamic forces create significant axial loads.

Cam-Roller Contact Modelling
Dedicated Cam and Roller subcomponents allow application-specific cam and roller definitions. Cam profiles can be described using grinding-machine-specific definitions for flat or cylindrical grinders or through polar coordinates.
The Roller component supports barrel-shaped geometry for representing crowned rollers. Contact discretization into multiple sections allows roller-barreling effects along the contact line to be included, while elasto-hydrodynamic lubrication modeling can calculate contact stiffness and friction.


Analytic and 1D EHL for Line Basic Contour Contacts
The Basic Contour Contact joint supports EHL modeling through numerical and analytical solutions of the Reynolds equation for pressure distribution and oil-film thickness.
The models account for elastic deformation, pressure-dependent viscosity, cavitation, and asperity interaction. These capabilities support more detailed analysis of mixed lubrication regimes, friction, wear, efficiency, durability, NVH, and high-load applications such as cam-follower systems.

New Oil Splash Outflow Boundary Condition for EHD+T
EXCITE M introduces an oil-splash outflow boundary condition for thermal EHD calculations. It is available for EHD+T models using thermal calculation mode with bearing structures where enlargement toward the edges is activated.
The boundary condition represents the effect of bearing oil splashing out of the lubrication region over a defined length of the bearing structure.

Export AVL EXCITE M Models as Python Script
EXCITE M can export an entire model or selected model components as Python scripts using the EXCITE M Python API. The generated script can reproduce the selected model state with configurable levels of detail and can serve as an entry point for users developing automation or extending models through scripting.
Scripts can be prepared for standalone execution with the sdt_python interpreter or executed through the Live Scripting pane during an interactive GUI session. Users can choose whether less critical model details are omitted in favor of default settings.

Support for REXS Version 1.7
REXS import now supports version 1.7, extending model exchange with third-party CAE and design applications. JSON-based REXS files are supported in addition to the existing XML format.
REXS 1.7 adds standardized support for additional components, including thrust roller bearings, radial slider bearings, and spline gear connections.


AVL FIRE M
AVL FIRE M provides CFD-based simulation capabilities for powertrain development, with the 2026 R1 feature set extending battery, fuel-cell, electrolyzer, and internal-combustion-engine modeling.
Batteries
Battery Thermal Runaway on GPUs
GPU performance for simulations using the Species Transport Module has been improved. The enhancement applies to battery thermal-runaway simulations as well as other flow-based applications. The supplied comparison reports approximately 25% speedup for the illustrated battery thermal-runaway GPU case relative to the referenced 2025 R2 release.

Particle-Induced Risk of Electric Breakdown
A new tunable methodology evaluates the risk of particle-induced electrical breakdown within electrode gaps. Local electric-field enhancement is represented through a distance-based correlation that reaches its maximum near either electrode and minimum near the midpoint.
The empirical formulation accounts for particle radius and a global scaling factor. Particle breakdown field strength is calculated using the correlation established by Hara et al. (1977), with user-defined parameters providing additional flexibility.

Temperature Dependency of Maximum Capacity
The equivalent-circuit battery model can now use a temperature-dependent maximum capacity. When temperature dependency is included during battery parameterization, the resulting relationship is transferred to the GUI and applied by the solver.
Fuel Cells and Electrolyzers
Porosity Media In Fuel Cell and Electrolyzer Simulations
FIRE M can now activate the Porosity Module and Fuel Cell/Electrolyzer Module simultaneously. Porous structures can therefore be incorporated into fuel-cell and electrolyzer simulations to represent effects such as pressure drop.
Pressure-drop formulations including the Forchheimer model can be applied to represent nonlinear flow behavior. Heat transfer between solid and fluid phases can be adjusted for individual porous domains, and Knudsen diffusion can be enabled for each porous medium to model gas transport in fine-pore structures.
Improved AEM and Alkaline Electrolyzer Modelling
For AEM and alkaline electrolyzers, ion concentration is handled differently within the Butler-Volmer formulation and is incorporated into exchange current density and the Nernst equation. AEM modeling also includes improved mass transfer between liquid electrolyte and ionomer.
The mass-transfer coefficient is accessible through the property database and can be specified separately for adsorption and desorption. Donnan potential is included in ion mass transfer. When liquid electrolyte is supplied to the cell, electrochemical reactions can occur directly in the liquid phase according to liquid ion concentration. External current is transferred into ionic current through electrochemical reactions in the ionomer and liquid phase, with the distribution related to liquid volume fraction in the catalyst layer. Ionic conductivity in the ionomer can also be defined as a function of ion concentration.

3D Reaction Zone for Solid Oxide Fuel and Electrolyzer Cells
SOFC and SOEC simulations can represent the electrochemical reaction zone as either a 2D surface or a 3D volume. The update also introduces ionic conductivity in porous solids and volumetric exchange current density, enabling more detailed representation of ionic transport and reaction distribution throughout the electrochemical volume.

Generalized Domain Detection and Potential Initialization for Fuel Cell and Electrolyzer Applications
Domain detection and potential initialization have been generalized to handle less conventional geometries, including parallel-connected cells and electrodes containing multiple bipolar plates and gas-diffusion layers. The algorithms are therefore less dependent on specific geometric assumptions.
Mesoporous substructure model for PEMFC catalyst layers
FIRE M introduces a mesoporous substructure model for PEM fuel-cell catalyst layers alongside the existing Agglomerate and Macro-Homogeneous models. The model permits material changes, such as carbon-support changes, without requiring recalibration.
Compared with the other catalyst-layer approaches, the mesoporous model provides more detailed behavior in high-current-density operation and greater sensitivity to humidity variations.
Knudsen Diffusion in Porous Media
Knudsen diffusion extends the multicomponent diffusion model for situations where the mean free path of gas molecules is comparable to or greater than pore diameter. Under these conditions, molecule-wall collisions become dominant.
The capability is particularly relevant to porous materials with nanoscale pores, including SOEC electrodes, and provides additional detail for transport modeling in porous electrode structures.
ICE-based Powertrains
New Solution App For In-Cylinder Flow Modelling
FIRE M introduces a solution app for generating and executing models covering in-cylinder flow, fuel injection, air-fuel mixing, ignition, combustion, and emissions. A guided interface organizes preprocessing and simulation setup into a structured sequence.
Users first select an engine working principle, including Spark ignited, Compression ignited, Pre-chamber, Port injection, Low pressure direct injection, or High-pressure direct injection. Fuel selection supports common fuels as well as customized multi-component fuel definitions.
The workflow then collects CAD geometry, intake and exhaust valve information, port counts, and model selections. The selection process provides visual feedback and allows users to interact with the identification of relevant model regions.

Additional setup data includes cranktrain information, compression ratio, and valve-lift curves.

Fuel-injection geometry can be defined through nozzle position and axis, injection-hole count and arrangement, spray-cone angle, injection timing, and injection rate. The workflow does not require users to enter numerical model parameters at this stage.

The injection geometry is used to generate a dedicated spray block with a structured grid intended to reduce numerical effects during fuel-spray simulation.

After initial and boundary conditions are defined, the application generates the simulation model using the selected inputs. Preconfigured numerical setups are matched to the chosen engine type, working principle, and fuel, while users retain access to mesh and simulation settings for further adjustment.
A major workflow change is that model generation and simulation can proceed together, with the FIRE M solver initiating mesh generation during model execution. Users can still use the traditional approach of generating the mesh in advance, inspect the meshing configuration, or generate meshes for selected crank angles before running the complete simulation.
The solution app streamlines setup without removing the underlying modeling flexibility. Existing FIRE M workflows and model parameters remain available for users who require detailed manual control.
New Multi-Component Cavitation Model For Simulating Diesel Blends
FIRE M extends its existing multi-component flash-boiling capabilities with a model for multi-component diesel injection into chambers at approximately 50 to 100 bar. Under these conditions, phase change can begin inside the injector, where gas bubbles form within the liquid fuel.

The model represents evaporation according to differences in partial pressure. In the cavitation region, the pressure difference is based on component saturation pressure and liquid partial pressure. In the flashing region, it is based on saturation pressure and the fuel component's partial pressure in the surrounding gas mixture.

The model has been applied to injector-flow simulations using diesel/FAME-S blends at 10:90, 50:50, and 90:10 ratios. Because FAME-S has lower saturation pressure and is less volatile than diesel, the model can distinguish cavitation behavior among the individual blend components.
AVL VSM
AVL VSM extends vehicle-system simulation with additional modeling for off-road mobility, ride and comfort, parameter customization, braking, and tire temperature.
More Realistic Off-road Simulation
The enhanced off-road modeling supports fully three-dimensional terrain in office and driving-simulator environments. Vehicle response can account for uneven, deformable, and variable surfaces, including steep gradients, obstacles, dirt roads, sand, fields, mud, and snow.
The VSM soft-soil tire model represents sinkage, traction limits, and soil-tire interaction. The capability also supports multi-axle vehicles and special-purpose and security-and-defense applications, including heavy-duty and articulated configurations.

Improved Ride & Comfort Simulation
Ride and comfort simulation has been refined through updated suspension and vertical-dynamics modeling. New vertical compliance configurations improve representation of road inputs and vehicle-body response in the frequency range associated with perceived ride quality.
Following the external tire integration introduced in VSM 2025 R2, the 2026 R1 release supports the latest tire models for more detailed tire-road interaction and analysis of harshness and vibration behavior.

Streamlined Experience for Customizing Parameters
VSM supports custom-model parameter integration through FMU and Simulink-based extensions. Custom parameters can be configured directly within the software GUI without requiring external preprocessing.
The workflow supports optimization and DoE studies and includes a parameterization check that validates model and parameter compatibility before simulation.
Brake Control and Tire Temperature Model
The hydraulic brake-delay model for all applications and the tire-temperature model for sports-car applications have been refined to better represent their effects on vehicle performance.


AVL ChatSDT, AVL IMPRESS M, AVL EXPLORE ChatSDT - AVL's AI-Powered Customer Support Assistant
Active Model and Selected Elements Referencing in ChatSDT
ChatSDT can reference the active model and selected elements through natural-language expressions such as "the model", "current model", "this subsystem", and "selected elements". This allows users to ask questions and inspect relevant models or elements without manually describing their context.

AVL IMPRESS M Result Visualization and Reporting
Operating Point Shown on Input Map
When an input map such as a charger performance map is displayed as a 2D surface chart, time-dependent curves can be added to show the operating point. During animation, the operating point moves across the map and leaves a trace representing its previous positions.

Design of Experiments and Optimization
Introduction of Adaptive DoE in AVL Simulation Desktop
AVL Simulation Desktop expands its Optimization functionality with Adaptive Design of Experiments. Instead of selecting all sampling points before running simulations, Adaptive DoE evaluates existing results and selects additional points according to where they provide the most useful information.
This iterative, machine-learning-driven approach is intended to build surrogate models and investigate optimal system behavior while reducing the number of required simulation runs.

AVL EXPLORE - Data Analyses and Surrogate Modeling
Data Access and Analysis Extensions - from Simulation DOE and via FMU
The integration between SDT Client Simulation and AVL EXPLORE provides direct access to data generated by DoE and optimization runs. Parameter and KPI run tables generated in Simulation Desktop can be selected directly through the EXPLORE Dataset Import interface.

EXPLORE can also visualize and analyze FMUs when the original dataset is unavailable. The Intersection Description provides input-output influence analysis, showing how individual input variables affect output variables and exposing model sensitivity.



AVL Advanced Simulation Technologiesprovides tools for engine and powertrain development across concept, design, simulation, and validation stages. In the concept phase, AVL CRUISE M can be used to configure conventional and electrified powertrains, investigate fuel consumption and emissions, evaluate transmission concepts, and develop gear-shifting strategies.
CRUISE M also supports thermal-management strategy development for engines and aftertreatment systems and can be used to assess the emissions-reduction potential of electrified auxiliaries. During detailed development, AVL FIRE and AVL CRUISE M Engine support combustion optimization for efficiency and raw NOx and particulate emissions.
Coupled fluid-structure simulations with AVL FIRE M provide information about thermal loading in components such as cylinder heads, exhaust valves, and water-cooled exhaust manifolds. AVL EXCITE supports low-friction powertrain development as well as durability and NVH analysis for conventional and hybrid systems. Its e-machine joints also support analysis and optimization of electrified transmissions for NVH and gear-engagement behavior.
For validation, real-time-capable AVL CRUISE M models based on detailed component simulation results can support control-system development in office, SiL, and HiL environments, as well as plant models for powertrain hardware validation under virtual RDE conditions.
AVLis a research and development company providing mobility engineering, testing, and simulation technologies for automotive OEMs and Tier-1 suppliers. Its activities cover passenger-car and commercial-vehicle applications, with engineering and simulation technologies spanning vehicle, powertrain, and related development processes.

System Requirements

System Requirements:Windows & Linux **
Supported Architectures:x64

Home Page

www.avl.com

Product Information

• Software Name: AVL Simulation Suite
  
• Version:2026 R1.1 *
  
• Architecture:x64
  
• Languages:english
  
• License type:Full Version
  
• File Size:14.7 Gb
  

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