Currently, hybrid and electric drive control systems are being developed for many types of platforms in the aerospace, automotive, and commercial vehicle industries. These systems use battery management systems (BMS), amongst other systems, to handle their demanding power needs.
However, the development of such technologies brings increased system complexity, evident in the platform variants, and even more so in the control algorithms of various electronic control units (ECUs).
Increased system complexity poses new challenges for software design and ECU system validation, mandating the need for simulation tools that can easily handle the inherent system complexity, while providing cost-effective, industry-proven verification tools and processes.
These simulation and testing tools and processes must be capable of providing support for model-based design (MBD) at various stages in the process, from control concept simulation through final target system acceptance. The processes for MBD using model-in-the-loop (MIL), software-in-the-loop (SIL), and hardware-in-the-loop (HIL) must take advantage of synergies in tools used throughout the process.
HIL systems are of particular interest for the validation of electric-drive (e-drive) and BMS control systems. This validation process involves specific implementation techniques for model processing and interfaces in real time, along with critical power interface and electrical hardware functionality.
The market for e-drive and hybrid systems has mandated advanced control for integration of these electric machines with modern powertrain technology and cutting-edge energy storage systems.
BMSs play a pivotal role in these systems as they control the energy storage and facilitate the practicality and safety of e-drives and hybrid vehicles. Motor controller technology has also demanded changes in the component and integration development and test systems as the simulation of the motors necessitates higher-levels of computation and precision to yield accurate closed-loop simulation results.
These systems also tend to utilize distributed ECUs, which adds yet another level of increased complexity for integration testing and development.
However, e-drive ECU testing requires specific types of hardware, depending on the interfaces for test. BMS systems also require very specific hardware and modeling approaches, depending on the distribution of components within the energy control ECUs.
E-drive systems use both motor speed and current to close the loop, so the details of these interfaces and power loads must be considered. These control loops in electric drive applications require a high-speed real-time dynamic response, which entails the use of higher-fidelity models with stable control dynamics that can close the loop. The required time resolution for signal measurement is in the sub-µsec range, and these measurements have to fit to a model of the power electronics where switching delays and dead times are handled.
Also, different applications, such as sensorless brushless dc (BLDC) motors necessitate the use of specific interfaces for back-EMF simulation to ensure proper testing functionality.
Battery cell simulation testing is critical to validate strategies for control of cell balancing across multiple cells or cell stack subsystems. Different battery chemistries may be controlled or monitored by BMSs (Li-Ion, Ni-MH, Pb, etc.), so models need to take these characteristics into account. There are also constraints with simulating many cells in real-time with simultaneous update rates, along with simulation of corresponding temperature sensors.
The cells are generally connected in series, so many cells or cell subsystems exist at high ground potentials, which need to be handled with proper galvanic isolation. The major requirement for this cell simulation is accurate voltage resolution accuracy (mV range) with low drift.
To adequately simulate electric motors, the models must be capable of running in real time with the proper precision to allow for testing at either the signal or the power level, depending on the type of system to be tested. There are options for this type of simulation and testing, depending on the physical characteristics of the motors and the power electronics.
To test BMS ECUs, high-precision hardware must be used for cell simulation, along with the proper functionality to allow for tests of balancing mechanisms and provide proper high-voltage and ECU communication interfaces. The real-time calculation requirements of these systems are also very demanding, whether they are high-speed motor load simulation or multicell stack simulation. This necessitates the use of validated systems that can handle this calculation and interface functionality.
It is also important to consider the safety requirements for these systems, especially when considering the high voltages and currents that may be present in inverter motor interfaces and battery cell stacks.
There are also specific applications that may require the use of special testing hardware interfaces and real-time model control to adequately validate system performance or diagnostics health management.
Demanding needs of automotive, aerospace, and commercial vehicle applications has been the driving force for the creation of these interfaces, since the considerations for safety and potential damage to expensive hardware have mandated the use of proper functional testing prior to any actual hardware integration.
The outlook for testing of these systems can take advantage of virtual-ECU testing capability in several ways.
The core software for motor controllers and BMS units can be component tested in MIL and SIL, enabling the development of tests that can be used in the HIL environment. These control systems may also use multiple controllers, and these systems can be tested prior to hardware availability in the HIL environment, if the core software for the missing ECUs is run as a virtual ECU.
These types of features and functions entail the need for standard interoperability with tools and the virtual ECU and HIL environment.
This article is based on SAE technical paper 2012-01-2144 by Jace Allen, dSPACE.