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The software design of this new engine control unit is based on a unique and homogenous torque structure. All input signals are converted into torque equivalents and a torque coordinator determines their influence on the final torque delivered to the powertrain. The basic torque structure is independent on the type of fuel and can be used for gasoline, diesel, or CNG injection systems. This allows better use of custom specific algorithms and facilitates reusability, which is supported by the graphical design tool that creates all modules using automatic code generation. Injection specific algorithms can be linked to the software by simply setting a software switch.

The aim of this work is to propose modifications to the managing of the 1st generation Common Rail injectors in order to reduce actuation time towards multiple injection strategies. The current Common Rail injector driven by 1st ECU generation is capable of operating under stable conditions with a minimum dwell between two consecutive injections of 1.8 ms. This limits the possibility in using proper and efficient injection strategies for emission control purposes. A previous numerical study, performed by the electro-fluid-mechanical model built up by Matlab-Simulink environment, highlighted different area where injector may be improved with particular emphasis on electronic driving circuit and components design. Experiments carried out at injector Bosch test-bench showed that a proper control of the solenoid valve allowed reducing drastically the standard deviation during the pilot pulses.

This research was to model a 6×4 tractor-trailer rig using TruckSim and simulate severe braking maneuvers with hardware in the loop and software in the loop simulations. For the hardware in the loop simulation (HIL), the tractor model was integrated with a 4s4m anti-lock braking system (ABS) and straight line braking tests were conducted. In developing the model, over 100 vehicle parameters were acquired from a real production tractor and entered into TruckSim. For the HIL simulation, the hardware consisted of a 4s4m ABS braking system with six brake chambers, four modulators, a treadle and an electronic control unit (ECU). A dSPACE simulator was used as the “interface” between the TruckSim computer model and the hardware.

A physics-based simulation program developed by IAV is used to calibrate the torque structure and cylinder charge calculation in the electronic control unit of SI engines. The model calculates both the charge cycle and combustion phase based on flow mechanics and a fractal combustion model. Once the air mass in the charge cycle has been computed, a fractal combustion model is used for the ongoing calculation of cylinder pressure and temperature. The progression of cylinder pressure over the high and low-pressure phases also provides information on engine torque. Following the engine-specific calibration of the model using elemental geometric information and reduced test bench measurements, the physical engine properties can be simulated over the operating cycle. The calibrated model allows simulations to be carried out at all operating points and the results to be treated as virtual test bench measurements.

The development of energy efficient air conditioning systems for electric vehicles is an ever increasing challenge, because the cooling as well as the heating of the passenger compartment reduces the cruising range dramatically. Electric cars are usually equipped with a scroll compressor and a separate electric motor with appropriate power electronics. However, this solution is critical in terms of the installation space, the weight and also the costs. Therefore, an innovative and energy efficient drivetrain structure for electric vehicles was developed, which integrates the motor of the A/C-compressor directly into the drivetrain. Thus it is possible to switch off the compressor motor and to use the main motor for the drive of the compressor at certain driving situations. As a result, the operating point of the main motor can be shifted to a better efficiency.

Engine control units (ECUs) on heavy trucks have been capable of storing “last stop” or “hard stop” data for some years. These data provide useful information to accident reconstruction personnel. In past studies, these data have been analyzed and compared to higher-resolution on-vehicle data for several heavy trucks and several makes of passenger cars. Previous published studies have been quite helpful in understanding the limitations and/or anomalies associated with these data. This study was designed and executed to add to the technical understanding of heavy truck event data recorders (EDR), specifically data associated with a modern Cummins power plant ECU. Emergency “full-treadle” stops were performed at many combinations of load-speed-surface coefficient conditions. In addition, brake-in-curve tests were performed on wet Jennite for various conditions of disablement of the braking system.

The powertrain electrification is currently not only taking place in public road mobility vehicles, but is also making its way to the racetrack, where it’s driving innovation for developments that will later be used in series production vehicles. The current development focus for electric vehicles is the balance between driving power, range and weight, which is given even greater weighting in racing. To redefine the current limits, IAV developed a complete e-powertrain for a racing MX motorcycle and integrated it into a real drivable demonstrator bike. The unique selling point is the innovative direct phase-change cooling (PCC) of the three-phase e-motor and its power electronics, which enables significantly increased continuous power (Pe = 40 kW from 7,000 rpm to 9,000 rpm) without thermal power reduction. The drive unit is powered by a replaceable Lithium-Ion round cell battery (Ubat,max = 370V) with an energy storage capacity of Ebat = 5 kWh.

This paper details the advancements and outcomes of the NEXTCAR (Next-Generation Energy Technologies for Connected and Automated on-Road Vehicles) program, an initiative led by the Advanced Research Projects Agency-Energy (ARPA-E). The program focusses on harnessing the full potential of Connected and Automated Vehicle (CAV) technologies to develop advanced vehicle dynamic and powertrain control technologies (VD&PT). These technologies have shown the capability to reduce energy consumption by 20% in conventional and hybrid electric cars and trucks at automation levels L1-L3 and by 30% L4 fully autonomous vehicles. Such reductions could lead to significant energy savings across the entire U.S. vehicle fleet.

Electronic throttle control is increasingly being considered as a viable alternative to conventional air management systems in modern spark-ignition engines. In such a scheme, driver throttle commands are interpreted by the powertrain control module together with many other inputs; rather than directly commanding throttle position, the driver is now simply requesting torque - a request that needs to be appropriately interpreted by the control module. Engine management under these conditions will require optimal control of the engine torque required by the various vehicle subsystems, ranging from HVAC, to electrical and hydraulic accessories, to the vehicle itself. In this context, the real-time estimation of engine and load torque can play a very important role, especially if this estimation can be performed using the same signals already available to the powertrain control module.

Whereas the verification of non-safety-related, embedded software typically focuses on demonstrating that the implementation fulfills its functional requirements, this is not sufficient for safety-relevant systems. In this case, the control software must also meet application-specific safety requirements. Safety requirements typically arise from the application of hazard and/or safety analysis techniques, e.g. FMEA, FTA or SHARD. During the downstream development process it must be shown that these requirements cannot be violated. This can be achieved utilizing different techniques. One way of providing evidence that violations of the safety properties identified cannot occur is to thoroughly test each of the safety requirements. This paper introduces Evolutionary Safety Testing (EST), a fully automated procedure for the safety testing of embedded control software.

Electronic Throttle Control systems substitute the driver in commanding throttle position, with the driver acting on a potentiometer connected to the accelerator pedal. Such strategies allow precise control of air-fuel ratio and of other parameters, e.g. engine efficiency or vehicle driveability, but require detailed information about the engine operating conditions, in order to be implemented inside the Electronic Control Unit (ECU). In order to determine throttle position, an interpretation of the driver desire (revealed by the accelerator pedal position) is performed by the ECU. In our approach, such interpretation is carried out in terms of a torque request that can be appropriately addressed knowing the actual engine-vehicle operating conditions, which depend on the acting torques. Estimates of the torque due to in-cylinder pressure (indicated torque), as well as the torque required by the vehicle (load torque), must then be available to the control module.

As the development of autonomous vehicles rapidly advances, the use of convoying/platooning becomes a more widely explored technology option for saving fuel and increasing the efficiency of traffic. In cooperative adaptive cruise control (CACC), the vehicles in a convoy follow each other under adaptive cruise control (ACC) that is augmented by the sharing of preceding vehicle acceleration through the vehicle to vehicle communication in a feedforward control path. In general, the desired velocity optimization for vehicles in the convoy is based on fuel economy optimization, rather than driveability. This paper is a preliminary study on the impact of the desired velocity profile on the driveability characteristics of a convoy of vehicles and the controller gain impact on the driveability. A simple low-level longitudinal model of the vehicle has been used along with a PD type cruise controller and a generic spacing policy for ACC/CACC.

This paper describes an adaptive control strategy for improving the steering response of an automated vehicle steering controller. In order to achieve repeatable dynamic test results, precise steering inputs are necessary. This strategy provides the controller tuning parameters optimized for a particular vehicle's steering system. Having the capability to adaptively tune the steering controller for any vehicle installation provides an easy method for obtaining precise steering inputs for a wide range of vehicles, from small off-road utility vehicles to passenger vehicles to heavy trucks. The S.E.A. Ltd. Automated Steering Controller (ASC) is used exclusively in conducting this research. By recording the torque input to the steering system by the steering controller and the resulting steering angle during only a single test, the ASC is able to characterize the steering system of the test vehicle and create a computer model with appropriate parameters.

Conventional methods of physicochemical models require various experts and a high measurement demand to achieve the required model accuracy. With an additional request for faster development time for diagnostic algorithms, this method has reached the limits of economic feasibility. Machine learning algorithms are getting more popular in order to achieve a high model accuracy with an appropriate economical effort and allow to describe complex problems using statistical methods. An important point is the independence from other modelled variables and the exclusive use of sensor data and actuator settings. The concept has already been successfully proven in the field of modelling for exhaust gas aftertreatment sensors. An engine-out nitrogen oxide (NOX) emission sensor model based on polynomial regression was developed, trained, and transferred onto a conventional automotive electronic control unit (ECU) and also proves real-time capability.

IAV GmbH is currently developing a test case generator, which uses information from Simulink®/Stateflow® models to generate test cases automatically. These test cases can then be applied during software tests for an ECU to show conformance to the original model. Using predefined rules, test cases for individual blocks are generated and converted into test cases for a whole model. The test cases can be saved as a XML file. Then, this file can be converted into test script languages which are used by tools for test execution. With the test case generator, the time-consuming and error-prone task of manual test case definition can be automated, thus decreasing test expenses for each test while increasing test quality.

State-of-the-art powertrain concepts with automatic transmission must comply with increasingly stringent legislation on emissions and fuel consumption while fulfilling or surpassing customers' expectations as to driveability. In this respect, automated manual transmissions (AMT) and automated shift transmissions (AST) must compete with conventional automatic transmissions (AT) and continuously variable transmissions (CVT). In order to exploit the theoretical advantages of ASTs and put them into practice, complex ECU functions are needed to coordinate engine and transmission. Adaptive control, sophisticated clutch management and an intelligent shifting strategy allow shifting quality and shifting points to be simultaneously optimized to the effect that performance and comfort are increased while fuel consumption is reduced.

The Ohio State University Center for Intelligent Transportation Research (CITR) has developed three automated vehicles demonstrating advanced cruise control, automated steering control for lane keeping, and autonomous behavior including automated stopping and lane changes in reaction to other vehicles. Various sensors were used, including a radar reflective stripe system and a vision based system for lane position sensing, a radar system and a scanning laser rangefinding system for the detection of objects ahead of the vehicle, and various supporting sensors including side looking radars and an angular rate gyroscope. These vehicles were demonstrated at the National Automated Highway System Consortium (NAHSC) 1997 Technical Feasibility Demonstration in a scenario involving mixed autonomous and manually driven vehicles. This paper describes the demonstration, the vehicle sensing, control, and computational hardware, and the vehicle control software.

In this study, an adaptive control mechanism is proposed to design a silencer applying variable volume resonator concept. Transfer matrix method is used to calculate the transmission loss and evaluate acoustic performance of the proposed mechanism. Effects of damping factor, area ratio of expansion chambers are examined first for a fixed double chamber resonator. Then a two-dimensional search scheme is developed to find optimal piston position that achieves maximum transmission loss with minimal effort. This study shows that the proposed adaptive silencer can efficiently attenuate noise when comparing with a conventional fixed resonator.

This paper presents a 14 degrees of freedom vehicle model. Despite numerous software are nowadays commercially available, the model presented in this paper has been built starting from a blank sheet because the goal of the authors was to realize a model suitable for real-time simulation, compatible with the computational power of typical electronic control units, for on-board applications. In order to achieve this objective a complete vehicle dynamics simulation model has been developed in Matlab/Simulink environment: having a complete knowledge of the model's structure, it is possible to adapt its complexity to the computational power of the hardware used to run the simulation, a crucial feature to achieve real-time execution in actual ECUs.

This paper discusses the development of the 1997 Jeep Cherokee model for the National Advanced Driving Simulator's planned vehicle dynamics software, NADSdyna. Recursive rigid body formalism called the Real Time Recursive Dynamics (RTRD) developed by the University of Iowa is used to model the front and rear suspension mechanisms. To complement vehicle dynamics for simulator applications, subsystems that include tires, aerodynamics, powertrain, brake, and steering are added to the rigid body dynamics model. These models provide high fidelity driving realism to simulate severe handling maneuvers in real time. The soundness of the model does not only depend on the mathematics of the model, but also on the validity of the parameters. Therefore, this paper discusses thoroughly the methodology of parameters estimation. A generic model of cruise control is included.