Periodic Reporting for period 1 - DORNA (Development of high reliability motor drives for next generation propulsion applications)
Période du rapport: 2020-03-01 au 2023-10-31
This action, entitled “Development of high reliability motor drives for next generation propulsion applications”, is a 4-year research focused training program. It is aimed to form a coherent Research and Innovation Staff Exchange network so as to address technical challenges facing the electrifying transport industry, with a focus on high-reliability electrical traction drives.
Transport electrification has been considered as a major advancement to reducing CO2 emissions and improving energy efficiency. At the heart of the propulsion systems are electrical traction drives. But technological developments are still at an early stage. Industries are trying out different traction drive technologies. Permanent magnet synchronous motors, induction motors, reluctance motors and DC motors-based traction drives are all found in use while they have their inherent advantages and drawbacks. In academia and industry, there are no consensus on the best traction drive for a single application. Existing technologies cannot meet the ever-growing market needs for safe, fast, green and affordable transportation. Major challenges include demands for very high torque density, power density, fuel efficiency and fault tolerance, pushing the devices and components to their physical and material limits. Particularly operating motor drives at high speeds and harsh environments require a new mindset of component and system design for safety-critical high-reliability requirements, as well as multidisciplinary approaches to combine multiphysics (e.g. thermal, stress) with the conventional electromagnetic and electronic designs.
This program will bring together EU’s leading universities and industries, and utilise the latest technological discoveries in power electronics, motor drives, drivetrains and control, sensors and monitoring, communications, big data and artificial intelligence. The outcomes will be significant to impact on EU transport sector, EU research landscape and EU economy.
This is the first project of its kind to respond to the identified gaps and to address the challenges of electrifying the transport industry in a coordinated fashion. It proposes the following eight objectives:
O1) developing new designs of highly reliable PMSMs, IMs, and synchronous reluctance motors (SynRMs) utilising new materials, new manufacturing and new analytical methods.
O2) designing silicon and wide bandgap (WBG) device based high-frequency power converters utilising new design methods and analytical tools for reduced power loss and electromagnetic interference (EMI), and optimising power converter integration with WBG devices.
O3) establishing multiphysics powertrain models and implementing ageing models for performance optimisation and control.
O4) deepening new understanding of component fault mechanisms and failure models, developing fault-ride-through topologies and control strategies for traction drives in propulsion conditions.
O5) developing integrated designs of electrical motor drives, multiphase motors and multilevel converters for fault tolerant operation.
O6) setting up a real-time big data platform for parameter identification, digital twins for data monitoring, machine-learning for diagnostics and prognostics (D&P) over the service life.
O7) providing bespoke training programmes and secondments to early-stage researchers (ESRs) and experienced researchers (ERs); exposing them to cross-sector cross-disciplinary environments; equipping them with technical competence, employability and leadership skillset.
O8) strengthening synergies between participating organisations by sharing best practice, and promoting multi-disciplinary research and cross-sector knowledge transfer.
Transport electrification has been considered as a major advancement to reducing CO2 emissions and improving energy efficiency. At the heart of the propulsion systems are electrical traction drives. But technological developments are still at an early stage. Industries are trying out different traction drive technologies. Permanent magnet synchronous motors, induction motors, reluctance motors and DC motors-based traction drives are all found in use while they have their inherent advantages and drawbacks. In academia and industry, there are no consensus on the best traction drive for a single application. Existing technologies cannot meet the ever-growing market needs for safe, fast, green and affordable transportation. Major challenges include demands for very high torque density, power density, fuel efficiency and fault tolerance, pushing the devices and components to their physical and material limits. Particularly operating motor drives at high speeds and harsh environments require a new mindset of component and system design for safety-critical high-reliability requirements, as well as multidisciplinary approaches to combine multiphysics (e.g. thermal, stress) with the conventional electromagnetic and electronic designs.
This program will bring together EU’s leading universities and industries, and utilise the latest technological discoveries in power electronics, motor drives, drivetrains and control, sensors and monitoring, communications, big data and artificial intelligence. The outcomes will be significant to impact on EU transport sector, EU research landscape and EU economy.
This is the first project of its kind to respond to the identified gaps and to address the challenges of electrifying the transport industry in a coordinated fashion. It proposes the following eight objectives:
O1) developing new designs of highly reliable PMSMs, IMs, and synchronous reluctance motors (SynRMs) utilising new materials, new manufacturing and new analytical methods.
O2) designing silicon and wide bandgap (WBG) device based high-frequency power converters utilising new design methods and analytical tools for reduced power loss and electromagnetic interference (EMI), and optimising power converter integration with WBG devices.
O3) establishing multiphysics powertrain models and implementing ageing models for performance optimisation and control.
O4) deepening new understanding of component fault mechanisms and failure models, developing fault-ride-through topologies and control strategies for traction drives in propulsion conditions.
O5) developing integrated designs of electrical motor drives, multiphase motors and multilevel converters for fault tolerant operation.
O6) setting up a real-time big data platform for parameter identification, digital twins for data monitoring, machine-learning for diagnostics and prognostics (D&P) over the service life.
O7) providing bespoke training programmes and secondments to early-stage researchers (ESRs) and experienced researchers (ERs); exposing them to cross-sector cross-disciplinary environments; equipping them with technical competence, employability and leadership skillset.
O8) strengthening synergies between participating organisations by sharing best practice, and promoting multi-disciplinary research and cross-sector knowledge transfer.
Up to 8 Secondments have been conducted covering activities across workpackage#1 – workpackage#6.
Additionally the consortium has organised two summer-schools and two technical workshops, with a combined attendance in excess of 200 people, including academics, researchers, engineers from industry and policy makers.
1 conference publication has been published, with 3 journal articles under review.
DORNA website has been created and launched.
Research outcomes include:
WP#1: development of baseline machines for electric vehicles, including PM machines, Induction machines, and reluctance-type machines
WP#2: development of WBG-based power converters (DC-DC and DC-AC) with high switching frequency and high efficiency;
WP#3: development of multiphysics numerical models incorporating e.g. electromagnetic, thermal, and mechanical models
WP#4: development of correlation between early faults and measurable terminal quantities (fault signature)
WP#5: development of control methods of AC machines based on, for example state-space feedback;
WP#6: development of intelligent motion control strategies, based on sensor fusion method.
Additionally the consortium has organised two summer-schools and two technical workshops, with a combined attendance in excess of 200 people, including academics, researchers, engineers from industry and policy makers.
1 conference publication has been published, with 3 journal articles under review.
DORNA website has been created and launched.
Research outcomes include:
WP#1: development of baseline machines for electric vehicles, including PM machines, Induction machines, and reluctance-type machines
WP#2: development of WBG-based power converters (DC-DC and DC-AC) with high switching frequency and high efficiency;
WP#3: development of multiphysics numerical models incorporating e.g. electromagnetic, thermal, and mechanical models
WP#4: development of correlation between early faults and measurable terminal quantities (fault signature)
WP#5: development of control methods of AC machines based on, for example state-space feedback;
WP#6: development of intelligent motion control strategies, based on sensor fusion method.
WP#1 – through the future secondments aligned to WP#1 (also linked to parallel developments in WP#2-#6), the baseline machines established so far will be improved to meet the 2035 transport electrification roadmaps, including reaching power density metrics (kW/kg), cost-performance (€/kg). NEC requirement has been documented.
At the end of the project, WP#2 will produce novel predictive control strategies and new modulation methods to produce high quality voltage waveform with low frequency modulation index, minimises the motor-drive system losses and reduce EMI and leakage current for improved bearings lifetime.
WP#3 will develop 3D multiphysics computational platform, mechanical models on noise and vibration, and thermal models of high-speed machines, respectively.
WP#4 will develop new understanding of physics of failure in electrical machines and power electronic converters, models the failures in powertrains, investigates big data based intelligent condition monitoring and fault diagnostics for electrical powertrains.
WP#5 will investigate the issues associated with the integrated drives (mechanical drivetrain, motors and converters) and develop new topologies to improve the system reliability. It proposes multiphase machine electrical drives, control systems, speed observer structures dedicated especially to multiphase machines, new electrical machine constructions, power converters based on voltage or current source inverter structure dedicated to multiphase machines.
WP#6 will analyse big data which are generated from key components devices in the electrical powertrains, ranging from data acquisition, storage, to knowledge-based data analytics.
WP#7 will develop the training needs for all ESRs, arrange local training courses and the network-wide events, as well as arrange with the supervisors and mentors personalised training courses through local and secondment hosts.
WP#8 will secure that all the relevant information is properly disseminated internally and publicly. All beneficiaries aim to disseminate research findings to a wide audience and increase the scope of the research impact.
WP#9 will involve all beneficiaries to develop strategies and execute the programme.
More people will be enrolled in engineering through university open day and events in the public.
A new generation of engineers with experience being embedded in companies is being trained.
Engineers in companies from multinational corporations to SMEs are being trained on the latest technologies being developed within the academic partners.
At the end of the project, WP#2 will produce novel predictive control strategies and new modulation methods to produce high quality voltage waveform with low frequency modulation index, minimises the motor-drive system losses and reduce EMI and leakage current for improved bearings lifetime.
WP#3 will develop 3D multiphysics computational platform, mechanical models on noise and vibration, and thermal models of high-speed machines, respectively.
WP#4 will develop new understanding of physics of failure in electrical machines and power electronic converters, models the failures in powertrains, investigates big data based intelligent condition monitoring and fault diagnostics for electrical powertrains.
WP#5 will investigate the issues associated with the integrated drives (mechanical drivetrain, motors and converters) and develop new topologies to improve the system reliability. It proposes multiphase machine electrical drives, control systems, speed observer structures dedicated especially to multiphase machines, new electrical machine constructions, power converters based on voltage or current source inverter structure dedicated to multiphase machines.
WP#6 will analyse big data which are generated from key components devices in the electrical powertrains, ranging from data acquisition, storage, to knowledge-based data analytics.
WP#7 will develop the training needs for all ESRs, arrange local training courses and the network-wide events, as well as arrange with the supervisors and mentors personalised training courses through local and secondment hosts.
WP#8 will secure that all the relevant information is properly disseminated internally and publicly. All beneficiaries aim to disseminate research findings to a wide audience and increase the scope of the research impact.
WP#9 will involve all beneficiaries to develop strategies and execute the programme.
More people will be enrolled in engineering through university open day and events in the public.
A new generation of engineers with experience being embedded in companies is being trained.
Engineers in companies from multinational corporations to SMEs are being trained on the latest technologies being developed within the academic partners.