Case Studies

Development of a software-hardware complex: Elevator cabin motion drive controller

The electric motor manufacturer aimed to enter the market with integrated solutions and supply elevator factories directly with a complete set: electric motor and controller with a setup remote, bypassing intermediate aggregators.

The task was to develop a controller (both hardware and software) that was low in component cost and cheap to produce yet capable of competing in the market as both an Economy and Business segment solution. This required finding a compromise between several factors:
  • Production cost

  • Ownership cost

  • Software development cost

  • Software maintenance cost

IMPLEMENTATION ROADMAP:

Defined technical
specifications for control circuits, feedback circuits
Formulated requirements
for the Control System
Developed
the Electric Drive Control System
  • Achievements
    Achieved the targeted price level
    Secured 40% market share by 2021-2022 (800-1000 units per month)
  • Hardware
    Power 180W (Peak - S00W)
    Motor IPMSM
    MOSFET Power modules
    ARM Cortex M4
  • Software
    Advanced Field Oriented Control
    MatLab Simulink/Mex Bias Development Studio
    Fast-acting loop frequency 20kHz
    C

Upgrade of a software-hardware complex:
Elevator cabin motion drive controller

A previous version of the device was released as a two-board controller with a separate remote control.

Based on the operational experience of the previous version, it was required to develop a new unit with key functional additions:
  • Add a Bluetooth module to eliminate the need for separate remotes

  • Make the unit single-board with single-sided assembly to reduce production costs

  • Ensure software unification across different hardware platform versions

IMPLEMENTATION ROADMAP:

Planning new functionalities
Product certification
Defining technical specifications
Defining product characteristics
  • Achievements
    Increased market presence by
    creating a sub-brand with additional functionality
    Reduced dependence on key
    component supplies
  • Hardware
    Power 180W (Peak - S00W)
    Motor IPMSM
    MOSFET Power modules
    ARM Cortex M4
    Bluetooth
  • Software
    Advanced Field Oriented Control
    MatLab Simulink/Mex Bias Development Studio
    Fast-acting loop frequency 20kHz
    C

Development of the edge device for Telematics integrated into the IoT Cloud

Telematics - data from equipment. It allows the monitoring of the data from the vehicles in real time and controls the fuel consumption and the behavior of the driver. If the driver drives aggressively, advice could follow on how to behave better. For EVs, it can predict battery consumption and life, focusing on the distance.

Telematic data on the server side is good for splitting driver activity from the manager activity.

IMPLEMENTATION ROADMAP:

Choosing the data scope
Defining transfer protocol
Implementing client and server functionality
Testing
  • Achievements
    Reduced fuel consumption
    Increased driving safety
    Real-time monitoring of vehicles
    Created recommendations for optimizing driving safety and fuel consumption
  • TECHNOLOGIES
    Azure loT
    MQTT

Customized remote configuration of edge device

This feature allows to setup VCU (Vehicle Control Unit) from the could framework and thus perform batch configuration.

Security settings and IDs are specific for each particular VCU to be secured and identified - different vehicles could have different hardware or sets of internal devices (Truck/Bus). Customize for each type of vehicle. We need to change some configuration. Remotely, the operator can change some settings from the cloud, send them to the vehicle, and apply them.

IMPLEMENTATION ROADMAP:

Choosing the data scope
Defining transfer protocol
Implementing client and server functionality
Testing
  • Achievements
    Increased security level
    User can configure the device from the cloud from anywhere
  • TECHNOLOGIES
    Azure
    Python
    Bash

Quantum key distribution system

Hardware and software implementation of QKD cryptographic system based on the product E91 protocol. Simulating the QKD system and conducting real-world tests reveal challenges such as signal attenuation, eavesdropping attempts, and environmental factors.

The system allows safe distribution of symmetric keys. The operational challenge was a balancing key generation rates with the distance of transmission and the acceptable error rates is an ongoing concern.

IMPLEMENTATION ROADMAP:

Developing modified protocol based on E91
Hardware implementation of the protocol for a single channel
Software implementation for Tree like networks
Integration with other QKD vendors
  • Achievements
    Auto detection of channel parameters
    Key storage infrastructure
    Possibility to extend the network
  • Hardware
    Optical devices: lasers, photon detectors etc
    FPGA
    Tamper detector
  • Software
    Linux
    C++/Bash
    CI/CD pipeline