auto industry with cae value


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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 The 6 must-know hyperautomation trends


hyperautomation with cae value


While some businesses have fully embraced hyperautomation, others are still experimenting with it at the periphery to see how it will best impact their business. Experts predict that within the next two years, every firm will actively use at least three of the 20 central processes that underlie hyperautomation.

Regardless of your current position, the moment has come to set up your company for a future that fully embraces this collection of potent technology. Here are the major trends from Gartner's Top Strategic Technology Trends for 2022: Hyperautomation to consider when you develop your approach.

1. Mainstream Hyperautomation

As with most new technologies, hyperautomation was quickly adopted by a small number of large companies that were willing to invest a significant amount of money in their experiments. However, as technology advanced, costs decreased, making them more affordable for SMEs with tighter budgets. Hyperautomation service providers are offering smaller, more manageable solutions to better serve the needs of small- to medium-sized organizations.

2. Robotic process automation's commercialization

Vendors are shifting their efforts to expanding their top-tier solutions as RPA becomes a more "entry-level" product. To provide consumers with a one-stop-shop for things like analytics, process mining, machine learning models, and more, they are vying to offer a thorough hyperautomation catalog.

RPA's commercialization benefits all businesses, not just smaller ones. Larger firms can take advantage of this trend to vary their hyperautomation portfolio by utilizing high-end tools for complex operations and low-cost solutions for simpler jobs.

3. Low-code leaks into hyperautomation 

The abilities, passion, drive, and job scope necessary to conceptualize, design, develop, test, and produce technology as well as data and analytics solutions are what Gartner characterizes as being present in this new cohort. To thrive, this group of driven technology leaders will require the right resources and instruction. Vendors of hyperautomation will increase their investment in low-code AI solutions, enabling more general business users to access machine learning models. Teams of business technologists will receive more uniform training from organizations. Low-code tools will transition from a useful competitive advantage to the industry standard by 2024, when they will be used for roughly 70% of all development work.

4. A new era of digital twins

65% of decision-makers in the manufacturing sector anticipate using hyperautomation to create digital twins of their business processes in the upcoming years. The idea was inspired by NASA's Apollo mission, which involved building precise duplicates of the lunar module on Earth. This twin remained in the lab to serve as a precision engineering simulator while the other shot toward the moon.

Your operations are replicated in the digital world by a digital twin. You can test how increased production might wear on machinery, examine how varying speed limits for field representatives would affect gasoline expenses, and observe how a small adjustment to one operation will affect the ones that follow it. To accurately reflect real-world situations, digital twins need an abundance of data, and hyperautomation is the ideal data hog to support this trend.

5. redesigning teams for the future of automation

During the most challenging times of the pandemic, automation kept many businesses viable. Many employees are displeased by the growing number of bots performing tasks that once belonged to human staff members as business resumes as usual. Their concerns aren't wholly unjustified, it's true—by 2025, automation is predicted to replace one in three jobs. On the other hand, artificial intelligence is anticipated to create more employment than it will eliminate. By the same year, according to Gartner, AI is expected to generate two million net-new employment. These new positions will appear at both ends of the spectrum: at the entry-level and in highly skilled, visionary senior management.

Revisions to roles are being made by savvy firms to get their staff ready for the impending transformation. Gartner also advises businesses to begin developing "fusion teams" rather than viewing the hyperautomation software package as a threat. These hybrid teams combine technology with a human employee's business subject expertise.

6. automated systems that go beyond routine chores

Executives are investigating how hyperautomation might function alongside human thought leaders in non-routine jobs, as well as how automation has been a godsend for increasing efficiency among repetitive, routine tasks. They are urging their teams to begin considering the major problems they may pursue with the aid of AI, rather than lamenting the loss of menial, repetitive jobs to a bot. Human employees should not be seen to be extinct as a result of AI activity; rather, it should be seen as a tool to enhance human skill sets with intelligence and insight that cannot be obtained manually.

Companies can no longer delay the implementation of hyperautomation. It is now a common strategy accessible to businesses of all sizes, not just the technorati elite.



Are you a Gartner customer? Get your copy of
Top Strategic Technology Trends for 2022: Hyperautomation

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