Embedded Engineering

Our Experience in Embedded Engineering

Embedded Engineering services involve the design, development, and optimization of hardware and software systems that are integrated into electronic devices. These services cater to a wide range of industries, including automotive, healthcare, consumer electronics, industrial automation, and IoT. By leveraging microcontrollers, sensors, real-time operating systems, and communication protocols, embedded engineers create customized solutions that enhance device performance, reliability, and functionality.

Model Base Design

  • Control Algorithm Development
  • Algorithm Refinement & Verification
  • Floating Point Model
  • CAN Communication protocol
  • Integrate generated code with handwritten software
  • Phased migration of legacy components
  • Legacy to Model-based conversion
  • Tool chain and automation tools for migration process to MBD
  • Automatic code Generation
  • Code generation & Integration
  • Model Optimization & Industry standard compliance
  • Model checking for production code worthiness
  • Plant Modeling
  • MIL, SIL, PIL Testing of the MATLAB model by comparing the legacy code

Software

  • Motor Plant Modeling, Inverter Modeling
  • PID Control Parameters Tuning
  • Model based design and development
  • Board support package design and development
  • Boot loader
  • CAN Communication protocol
  • Control algorithm simulation
  • AUTOSAR Compliant Software/MCAL
  • Plant & controller modeling
  • Executable specification development
  • Auto-code generation
  • ECU Software
  • Control Software
  • Platform software
  • IVI system
  • Functional safety complying to Automotive Standard- ISO26262
  • Rapid Design & Development of Solution from scratch, understanding pain points, refining the product requirements during the course, resulting in optimal cost-effective solution
  • Strong team of 60+ Engineers
  • Experience in engineering of powertrains, battery management systems, and advanced algorithms
  • Cost benefits through productivity tool and process improvement
  • Matlab Simulink
  • IBM Doors
  • PTC Integrity
  • LDRA
  • Rhapsody
  • Dspace Tool Set
  • Vector Tool Set
  • Artisan
  • Trace 32
  • GIT
  • Kubernetees
  • Cute
Matlab Simulink
IBM Doors
PTC Integrity
LDRA
Rhapsody
Dspace Tool Set
Trace 32
GIT
Kubernetees
C, Embedded C
Java
C++
Python
Verilog
MAAB guidelines

Full service information management

What is meant by Digital & AI Capability?

It refers to the tools, technologies, skills, and processes that organizations use to leverage digital systems and artificial intelligence for better decision-making, automation, and innovation.

Why is Digital & AI Capability important for businesses?

It helps businesses improve efficiency, enhance customer experiences, drive innovation, and stay competitive in a rapidly evolving market.

What are examples of Digital & AI capabilities?

Examples include data analytics, machine learning, robotic process automation (RPA), cloud computing, IoT (Internet of Things), and intelligent chatbots.

How can a company build its Digital & AI Capability?

By investing in talent, modernizing IT infrastructure, adopting AI tools, integrating data across systems, and promoting a digital-first culture.

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contact us

Tell Us : business@suyan-group.com