Altair > Case Studies > Creating a Safe and Sustainable Fun Utility Vehicle (FUV) with IoT

Creating a Safe and Sustainable Fun Utility Vehicle (FUV) with IoT

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Technology Category
  • Analytics & Modeling - Digital Twin / Simulation
  • Robots - Autonomous Guided Vehicles (AGV)
Applicable Industries
  • Automotive
  • Transportation
Applicable Functions
  • Product Research & Development
Use Cases
  • Transportation Simulation
  • Vehicle Performance Monitoring
Services
  • Testing & Certification
About The Customer
Arcimoto is a company that was founded in 2007 with the goal of catalyzing a shift towards a sustainable transportation system. The name Arcimoto means 'Future I Drive', reflecting their aspiration to develop new technologies and patterns of mobility that enhance environmental efficiency, sustainability, and affordability. They began work on the SRK Generation 8, an all-electric commuter vehicle, in January 2015. This Fun Utility Vehicle (FUV) combines the fun-factor and efficiency of a motorcycle with the stability and protection of a car, offering a unique transportation option for urban dwellers. The FUV boasts 230MPGe and can reach top speeds of 80mph.
The Challenge
Arcimoto, a company founded in 2007 with the mission to build sustainable transportation systems, faced a challenge in creating an optimized platform for their Fun Utility Vehicle (FUV). The FUV was designed to be a three-wheeled, all-electric commuter vehicle that combined the fun-factor and efficiency of a motorcycle with the stability and protection of a car. The challenges included creating a space frame enclosure for protection, a rear swing arm that could handle load requirements, and maintaining the visual design of the vehicle. As a start-up, Arcimoto also faced budget constraints and the pressure to generate interest in the marketplace and among investors. The engineering team had to ensure the vehicle was strong enough to withstand road conditions, and they also wanted to adhere to cross-industry safety tests, such as the roof crush test, to instill confidence in their product.
The Solution
Arcimoto used Altair's HyperMesh and RADIOSS software to overcome their design and safety challenges. HyperMesh provided an environment for rapid model generation, allowing Arcimoto to perform analysis in OptiStruct in a time-efficient manner. This helped them evaluate the strength of different parts of the FUV, such as the rear swing-arm, and validate their decision to use tubular materials for the design. For the roof crush analysis, the team used HyperMesh to model a complex roll cage and RADIOSS to perform the simulations. This allowed them to test different thicknesses and compare against a baseline, giving them confidence in their design's ability to withstand the weight of the test. The use of these software tools enabled Arcimoto to achieve repeatable and accurate results, reduce simulation cycle times, and evaluate multiple design scenarios, leading to better design decisions.
Operational Impact
  • The use of Altair's HyperMesh and RADIOSS software not only helped Arcimoto overcome their design and safety challenges but also enabled them to make better design decisions. The software allowed for rapid model generation and efficient analysis, enabling the team to validate their design choices and ensure the vehicle's strength and safety. The ability to perform multiple simulations and tests gave the team confidence in their design and its ability to withstand various road conditions and safety tests. This, in turn, allowed them to create a strong market message backed by data, enhancing their credibility and appeal to potential investors and customers. Furthermore, the software helped the team work within their budget constraints, demonstrating the value of simulation in start-up environments.
Quantitative Benefit
  • The FUV boasts a fuel efficiency of 230MPGe, significantly higher than traditional vehicles.
  • The FUV can reach top speeds of 80mph, making it a viable option for urban commuting.
  • The use of simulation software reduced cycle times, allowing for quicker design iterations and decision making.

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