Altair > Case Studies > Improving Electric Vehicle Interior Quality with IoT: A Case Study on NEVS

Improving Electric Vehicle Interior Quality with IoT: A Case Study on NEVS

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Technology Category
  • Analytics & Modeling - Digital Twin / Simulation
  • Robots - Autonomous Guided Vehicles (AGV)
Applicable Industries
  • Automotive
  • Buildings
Applicable Functions
  • Product Research & Development
  • Quality Assurance
Use Cases
  • Transportation Simulation
  • Virtual Prototyping & Product Testing
Services
  • Testing & Certification
  • Training
About The Customer
National Electric Vehicle Sweden (NEVS) is an electric vehicle and technology developer formed from the experienced engineering teams of SAAB Automobile. The company’s vision is to shape mobility for a more sustainable future through the development of mobility services that provide a more engaging electric vehicle (EV) experience. In cooperation with its Chinese shareholders, NEVS is establishing a production and R&D joint ventures in the Tianjin Binhai Hightech Zone in Tianjin, as well as a brand experience center in Beijing. Thanks to the team’s experience of developing vehicles in the Saab Automobile era, NEVS are highly knowledgeable regarding the use of simulation technologies to lead the design process.
The Challenge
National Electric Vehicle Sweden (NEVS), an electric vehicle and technology developer, was facing a challenge in accurately simulating and eliminating squeak and rattle noise in the interior of their electric passenger cars. These noises, created when two parts come into contact or are displaced relative to each other, can lead to a perception of poor quality among vehicle occupants. The traditional process of building a prototype, testing material interaction, and correcting problems as they occur was proving to be lengthy and expensive. The company was eager to better understand and predict these phenomena to reduce interior noise and improve ride quality. However, the Interior Simulation Team had not yet used simulation strategies to predict and address squeak and rattle issues.
The Solution
NEVS approached Altair ProductDesign, with whom they had a long-standing relationship, to see if the interior quality issue could be tackled with simulation. Altair ProductDesign implemented Altair’s Squeak and Rattle Director (SnRD), a comprehensive set of services and software automations that rapidly identify and analyze design alternatives to eliminate the root causes of squeak and rattle in assemblies. The first stage was to build a base model for squeak and rattle risk analysis as a reference for the existing performance of the initial design. Risk areas identified at this early stage were communicated back to the design team and a series of design recommendations were proposed. The model geometry was updated based on these suggestions, and a further risk analysis was performed. Detailed investigations of the relative displacement profiles for dynamic behavior were documented, enabling the team to identify critical frequencies and find the optimum balance between global and local stiffnesses. Component level optimization studies were performed to guide the design team in improving the stiffness of key structures.
Operational Impact
  • The implementation of the Squeak & Rattle Director at NEVS has revolutionized their approach to interior quality control. The relative silence of an electric powertrain no longer masks rattling and squeaking noises, making their elimination a priority. The SnRD has enabled NEVS to identify S&R risk zones without physical prototypes, and provide valuable inputs to eradicate those risk areas to arrive at a more robust design. The required models are rapidly built and set up for analysis, with the results automatically post-processed, all while providing access to powerful and intelligent optimization technologies that identify improvements throughout the structure. This has not only improved the quality of the vehicle interiors but also the overall perception of the product.
Quantitative Benefit
  • Rapid identification of risk areas, accelerating development time
  • Reduced need for prototypes, leading to significant cost savings
  • Ability to explore the effect of different deviations that could result from the manufactured parts through sensitivity studies

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