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Lab is currently under construction (For engine test capability, click ARES link above)

Text Box: Automotive Controls Lab (ACL)
Text Box: Automotive Research Experiment Station (ARES)



Hardware-In-the-Loop (HIL) Simulation and Powertrain Control Development Station


Powertrain Controller


Rounded Rectangle: Cam Output
Rounded Rectangle: PWM Output
Rounded Rectangle: Crank Output
Rounded Rectangle: General Digital I/O
Rounded Rectangle: CAN Communication
Rounded Rectangle: Knock Sensor Rounded Rectangle: Fuel/Spark Measure
Rounded Rectangle: PWM Input
Rounded Rectangle: In-cylinder Comb

Breakout Box


Opal-RT Prototype Controller


MotoHawk Prototype Control Module


HIL Simulation Advantage

q Development cost reduction: using HIL simulator for both control hardware and software (strategy) development reduces engine dynamometer usage,  and hence reduces control strategy development cost.

q Short development cycle: control algorithm can be developed, implemented, and validated efficiently in the HIL simulation environment since it does not involved in actual hardware. Study can be done before the hardware is made.

q Flexible development environment: powertrain system model can be reconfigured easily in HIL simulation, allowing to study different powertrain system with different configurations.


Mean value or cycle-to-cycle engine model


Contact information:


Dr. George Zhu, Michigan State University, Mechanical Engineering

148 ERC South, East Lansing, MI 48824

(517)-884-1552, zhug@egr.msu.edu


HIL Application to Closed Loop Combustion Control (CLCC) Research


o Control algorithm development, implementation and validation for the following applications:


o closed loop ignition timing control (MBT, knock, …)

o maximum dilution/EGR rate control for reduced emissions and improved fuel economy

o engine valve timing optimization for improved combustion efficiency

o direct injection timing optimization

o and more








Fuel Injector Spray Diagnostics Station


Back-lit Spray Imaging

(LaVision’s SprayMaster Imaging System)


Aerometrics’ Phase Doppler Particle

(PDPA) Analysis


q Algorithms developed for sophisticated data analysis and image processing

q Test procedure and reporting follow the SAE GFISC J2715 test protocols & recommendations


Text Box: Typical output from Imaging Test: Various Spray Patterns

Injector Spray Penetration Characteristics


Flow Performance Test Stand (Static/Dynamic)


Typical Output from PDPA


q Laser sheet (Mie Scattering) and/or flood illumination

q Transient spray development, spray angle and                       penetration, pulse to pulse variation

q Optical patternation (spray pattern, symmetry, and cone quality)


q Simultaneous, point-wise measurement of spray drop size, velocity and volumetric flux

q Time-resolved or time-integrated with injector logic signal




Dr. George Zhu

Michigan State University

Mechanical Engineering

148 ERC South

East Lansing, MI 48824