auto industry with cae value

Automotive

We work side-by-side with our clients to shorten development time using the following deliverables:

  • High-fidelity modeling of chassis and powertrain dynamics
  • Multi-objective Design Optimization (MDO) - using Design Exploration to generate balanced solutions meeting desired performance for attributes such as noise, vibration, harshness (NVH), handling, ride, driveability, durability, and more.  
  • Automation of simulation processes to increase efficiency
  • Tire measurement for Durability, Handling and Ride applications
  • Driving Simulator hardware, software and services
  • Mechatronics simulation with connected mechanical and ADAS models
  • Process assessments to identify bottlenecks, define roadmaps, and maximize return on Computer Aided Engineering activities.

 

6 Use Cases for CAE Simulation in
Electric Vehicle Drivetrains


As electric vehicles take over a larger share of the automotive market, OEMs and suppliers alike need to make use of every tool at their disposal to improve the performance of their vehicles. At present, no tool is more essential than CAE simulation when it comes to helping manufacturers test the design of EM components and how they contribute to the structure, efficiency, and performance of a vehicle.

While a lot of attention is often focused on battery performance in EVs, the electric drivetrain also presents completely new engineering challenges that require extensive simulation in order to understand how interconnecting systems affect each other. From our experience working in the automotive industry, we have identified six key areas where simulation helps EV engineers improve drivetrain performance. Let’s take a closer look.

 

1. NVH

In automotive engineering, reducing NVH (noise, vibration, and harshness) is essential to providing a comfortable passenger experience. Combustion engines are significantly more noisy than electric motors, which might lead some to believe that NVH reduction doesn’t require the same level of care and attention. However, the noise of the combustion engine masks a lot of NVH issues that would otherwise be problematic. With the engine noise gone, passengers are more likely to notice outside noises, as well as sounds from the gearbox or coolant systems.The issues are similar for vibration. A vehicle that moves and shakes is disquieting to passengers, and gives an impression of low quality. While passengers expect vibration from a combustion engine, electric vehicles will still experience vibration conditions when they are on the road. These can be more noticeable to passengers, leading them to feel less satisfied with the vehicle.

These factors are what make NVH simulation in electric vehicles so important. CAE simulations can show how disparate parts work together to contribute to passenger experiences of NVH. These can then be remedied in the design.


2. Electric Motor Performance

Electric vehicles have typically lagged behind those with internal combustion engines (ICEs) in terms of power and performance. This has been a barrier to wider adoption, as improvements in motor and transmission performance have come at a tradeoff to battery longevity. However, newer EV technologies have increased the efficiency of electric powertrains, allowing them to compete with and even outperform their ICE counterparts.

Multiphysics simulations have been integral to these improvements, and can help automotive manufacturers develop even better designs. This can be particularly important in optimizing motor efficiencies with gear ratios, to improve performance on highways or during uphill driving.

3. Thermal Management

Proper thermal management keeps components operating at optimal efficiency, which results in less drain on the battery and greater range for the vehicle. Thermal management systems in electric vehicles are more complex than their ICE counterparts, as batteries must be either cooled or heated depending on operating conditions, and because EMs don’t generate any waste heat that might be used to warm the cabin.Analyzing the way motors, inverters, generators, and batteries work together to consume energy is an important part of thermal management. Simulations can be used to model the entire vehicle to better integrate these systems for more efficient use.

4. Lubrication

Electric vehicles require different lubricants than ICEs. Without fossil fuels and with fewer moving parts, these systems run cleaner, meaning the engine oils will collect fewer contaminants over time from burning fuel. However, EV motors operate at very high speeds, and still require both oil and coolant. And, while EV transmissions are different from ICEs, they do still require lubrication for the gear reducer.

Thus far, there is no one solution to which lubricants should be used for different EV transmissions. While some manufacturers use traditional transmission fluid, others are relying on grease bearings with oil lubricants. CFD simulation can help engineers understand which lubricants work best based on their design choices.

5. New Materials

A key strategy for improving fuel efficiency in electric vehicles is to reduce the weight of the vehicle itself. Increased strength and stiffness can also improve the responsiveness and speed of electric motors, leading to better operating conditions. However, for a manufacturer to move from traditional metals to new, lightweight alloys, they must be able to ensure that these new materials can withstand the strains of use within an electric vehicle.CAE simulation can show how these new materials behave when used in EV driveline components, from the motor to the gearbox to the structural housing, so that manufacturers can continue to find new and more effective materials for their vehicle designs.


6. Durability

The reputations of automotive manufacturers are made or broken on the reliability and longevity of their products. Premature failure of components leads to lost trust among consumers, as well as extra expenses for manufacturers in case of a large recall.

Using CAE simulation, engineers can create models to run fatigue tests and predict failure conditions for every component in the EV driveline. These simulations can help manufacturers determine repair schedules and write better warrantees for their vehicles.

CAE VAlue can support your simulation needs for electric vehicle drivetrains.
CAE VAlue offers CAE simulation support for OEMs and suppliers in two key ways. First, we are value-added resellers (VARs) of VI-grade simulation apps and driving simulators, Siemens Simcenter HEEDS and Amesim, SES-Agile Tire, and our own ParaMount bushing simulation tool. For manufacturers who hope to expand their CAE departments we offer support for using this software to set up custom workflows.

As CAE consultants, we bring our multidisciplinary expertise to the table, helping our clients find solutions to complex problems. We can perform CAE simulations for our clients, increasing the capabilities for those who do not have CAE engineers on staff, and expanding the capacity for those who need extra assistance during peak production times.

If you are looking for a CAE partner to help test designs for EV components, contact us

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intelligent and informed decisions, faster!

With process automation and design space exploration tools, simulation engineers can now evaluate hundreds or even thousands of designs, all while meeting tight product deadlines. However, efficiently analyzing this vast amount of data is crucial to provide engineers with deeper insights. These insights enable the engineer to identify the best design or thoroughly assess alternative options.

As we accelerate the design process to achieve innovation goals more quickly, we need a solution to interpret large datasets and make intelligent, informed decisions.

That solution is HEEDS POST.

 

heeds post processing 1

 

 

BENEFITS

  • Presents large datasets in a structured and organized manner, integrating multiple views on a single screen.

  • Enables real-time monitoring and control of data during the execution of a design study, with the ability to add additional information after the study is complete.

  • Offers customizable features and metrics for analyzing data mining results, with options to export animations, reports, and study outcomes.
  • Utilizes all data generated during a study to identify optimal designs and key designs of interest through advanced automated toolsets.
  • Provides efficient exploration of performance trade-offs and streamlines design reviews, enabling the discovery of correlations and sensitivities.

  • Enhances understanding of design performance, regardless of the number of competing objectives and constraints.

 

 

heeds post processing 2

 

 

TRANSFORMING DATA INTO ACTIONABLE INSIGHTS

HEEDS POST organizes all generated data into various visual formats, leveraging a comprehensive set of tools to help users gain insights and identify the optimal solution for their needs.

As the post-processing and data mining tool of HEEDS, HEEDS POST uncovers valuable insights from simulations, revealing the best solutions, trends, and high-performing alternatives. It is available both within HEEDS and as a standalone product for users’ data mining requirements. 

 

 

heeds post processing 3

 

 

KEY FEATURES OF HEEDS POST INCLUDE

• Plots
• Analysis tools
• Data sets
• Automated reports

Plots
Plots provide a wide range of 2D and 3D visual representations of data generated from automated workflows or imported datasets. Users can view default plots or create custom visuals to analyze data based on specific data mining requirements. Plots, visuals, and toolsets can be combined and customized on a single canvas for synchronized data interpretation. Various design concept views include:

Parallel Plot
• Displays highly dimensional data in an easily understandable 2D format.
• Facilitates quick and efficient trend analysis.

Design Table
• A tabular display of all data, providing a comprehensive overview.

History Plot
• Tracks parameter evolution throughout the design study.
• Highlights areas needing improvement.

Visualization Images
• Provides graphical comparisons between designs using native tools.

Analysis Tools
A broad selection of tools and techniques are available to automatically interpret data trends. These specialized toolsets leverage HEEDS' unique capability to discover and investigate data patterns using automated statistical methods, including the development of reduced-order models.

Data Sets
Data sets represent collections of designs with shared properties. Users can create and refine different data sets or down-select individual sets or families of solutions for quick comparisons. This is similar to node sets or element sets in simulation tools, allowing users to apply filters and rules manually as needed.

Automated Reports
Users can include their study data and set up report templates using interactive HTML reports, streamlining result reporting and distribution across their organization. This enables dynamic data visualization for review meetings without the need for a software license.

 

 

 

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