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:

1
Defined technical
specifications for control circuits, feedback circuits
2
Formulated requirements
for the Control System
3
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:

1
Planning new functionalities
2
Product certification
3
Defining technical specifications
4
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:

1
Choosing the data scope
2
Defining transfer protocol
3
Implementing client and server functionality
4
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:

1
Choosing the data scope
2
Defining transfer protocol
3
Implementing client and server functionality
4
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:

1
Developing modified protocol based on E91
2
Hardware implementation of the protocol for a single channel
3
Software implementation for Tree like networks
4
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