The laboratory intends to study model-based control strategies to increase life-cycle of multi-cell vehicular battery packs and improve the accuracy of the two vital battery parameters, i.e. state-of-charge (SoC) and state-of-health (SoH). The study includes advanced control-oriented models with reduced computational accuracy for the practical real-time integration in electric vehicles power trains.
The laboratory intends to study advanced control strategies of bi-directional power electronic converters using wide-band gap (WBG) switching semi-conductors like Silicon Carbide (SiC) and Gallium Nitride (GaN). The control and stability analysis of WBG-based circuits from the system viewpoint are still in infancy, and the lab investigate to implement practical control systems to reduce the switching losses and overall efficiency of the converter.
The laboratory intends to setup a workstation for studying multiple configurations in grid-connected and islanded modes of operation, hybrid AC and DC Microgrids, or even Microgrids clusters. The workstation facilitates real-time control, operation, and optimal energy management of renewable energy integration together with energy storage systems and consumption.
We seek experimental-research-oriented environment to test, develop and investigate fail-safe micro-grids operating autonomously specially in islanded mode. We also investigate the best solution for grid-connected microgrids in scenarios such increasing distributed generations and mass adoption of electric vehicles. To achieve our target, the core research for AC/DC microgrids is focused on the following:
- Modelling: We need inclusive models for all microgrid elements such as generators, energy storage systems, loads, power electronics converters, and electrical distribution networks. The models must describe the microgrid in local control levels such as power converter, connection level such as wireless sensor network (WSN), and global control level such as microgrid controller.
- Control and operation: Local, distributed, and hierarchical controllers are needed to provide best power quality and fast communication and handle the micro-grid elements with different frequency ranges, and time scales
- Distributed control and Multi-Agent Systems: This is a powerful tool for a micro-grid with no single point of failure and a balanced energy level between energy storage and generation.
- Networked control systems: To achieve the network stability and effectively manage the locally-installed distributed controllers in complex scenarios, networked control is needed with new mathematical tools for controllability and observability.
- Wireless sensor networks: It seems that WSNs is a suitable platform for smart-metering and networked control systems applied to the modern microgrids. To reduce network traffic, and increase the sensor battery life-time, different communication models, e.g. event-triggered models, have to be investigated.
- Power quality: To provide the best power quality, voltage and current harmonics and unbalances have to be suppressed. At the same time, the increasing use of DGs and EVs will result in over- and under- voltage problems. New technology needed to overcome these problems.
The laboratory intends to study wireless multi-sensory onboard calibration for particulate reduction and emission in internal-combustion petrol engines and diesel engines. We also seek novel model-based control solutions to increase the power of turbo-charged air-path system in hybrid engines.
The Laboratory is equipped with the powerful dSPACE real-time simulators as a enabling technology to study and analysis different models of physical systems and control strategies using hardware-in-the-loop (HIL) and rapid control prototyping (RCP). The dSPACE equipment of the laboratory are as follows:
SCLALEXIO – a powerful Multi-core and versatile hardware-in-the-loop (HIL) simulator that provides highly flexible channels, and a specialized I/O hardware. Control Desk Next Generation software let real-time simulation of Matlab/Simulink models, e.g. dSPACE Electrical Power Systems Simulation Package allows the real-time simulation of electrical models developed in SimPowerSystems. Read more.
MicroLabBox – a small all-in-one development system for rapid control prototyping (RCP). It comes with over 100 channels of different I/O types and a combination of real-time processor and FPGA functionality. Close-loop and open-loop control algorithms can be developed in Matlab/Simulink and implemented on the freely programmable FPGA of the MicroLabBox to achieve the fastest possible control sampling rate. RTI E-Motor Control blockset is used in combination with FPGA programming blockset to achieve the fastest possible control sampling rate of 16MHz for motor control. Read more.
DS1104 R&D Controller Board – a single PCI board system for real-time control development and rapid control prototyping (RCP). Currently, two PCs in the lab have this board installed and can be used as a real-time hardware for smaller control development in power electronics, electrical machines, drives, and robotics. Read more.
What is Real-time simulation?
Physical systems are continuous but controllers are digital or discrete. Imagine we want to control an internal combustion engine of a vehicle. In the engine control unit (ECU) the data is read from all the sensors (via DAC) with a specific sampling time. Control algorithm must finish its execution within the sample time. Therefore, each “step” of the control program must be started exactly one sample time or step size apart, and have to be finished the computation of each step within the sample time, i.e. before the next step starts, to send the processed data (via ADC) to actuators. This is a real-time system.
Digital control system for an engine management system
Real-time control timing
dSPACE real-time simulator for emulation, test and optimization of a control/plant model developed in Matlab/Simulink
Real-time simulation is the de facto engineering process for the development, test and validation of control systems in a variety of applications including but not limited to control and simulation of power electronic circuits, motor control, engine control, vehicle control, and robotics. There are two important steps in real-time implementation, Hardware-in-the-loop (HIL) simulation, and rapid control prototyping (RCP).
RCP is the design of control system when you simulate a model of the controller connected to an actual physical system (or plant). The image above illustrates the development process of a control system using RCP (read more in dSPACE website).
In Hardware-in-the-loop testing, the process is the opposite where the control hardware (embedded implementation) connected to the simulated model of the physical plant. The image above shows the HIL test of a multi-cell battery pack using dSPACE system. Very useful material about real-time simulation, digital signal processing (DSP), HIL and RCP can be found in Mathworks website .