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With the inception of model-based design and automatic code generation, many organizations are developing controls and diagnostics algorithms in model-based development tools to meet customer and regulatory requirements. Advances in model-based design have made it easier to generate C code from models and help software engineers streamline their workflow. Typically, after the software has been developed, the models are handed over to a calibration team responsible for calibrating the features to meet specified customer and regulatory requirements. However, once the models are handed over to the calibration team, the calibration engineers are unaware of how to calibrate the features because documentation is not available. Typically, model documentation trails behind the software process because it is created manually, most of this time is spent on formatting. As a result, lack of model documentation or up-to date documentation causes a lot of pain for OEM’s and Tier 1 suppliers.

The primary function of an airbag control module is to detect crashes, discriminate and predict if a deployment is necessary, then deploy the restraint systems including airbags and where applicable, pretensioners. At General Motors (GM), the internal term for airbag control module is Sensing and Diagnostic Module (SDM). In the 1994 model year, GM introduced its SDM on some of its North American airbag-equipped vehicles. A secondary function of that SDM and all subsequent SDMs is to record crash related data. This data can include data regarding impact severity from internal accelerometers and pre-crash vehicle data from various chassis and powertrain modules. Previous researchers have addressed the accuracy of both the velocity change data, recorded by the SDM, and the pre-crash data, but the assessment of the timing of the pre-crash data has been limited to a single family of modules (Delphi SDM-G).

Electro-hydraulic actuation has been used widely in automatic transmission designs. With greater demand for premium shift quality of automatic transmissions, higher pressure control accuracy of the transmission electro-hydraulic control system has become one of the main factors for meeting this growing demand. This demand has been the driving force for the development of closed loop pressure controls technology. This paper presents the further research done based upon a previously developed closed loop system. The focus for this research is on the system requirements, such as solenoid driver selection and system latency handling. Both spin-stand and test vehicle setups are discussed in detail. Test results for various configurations are given.

This paper presents a hardware-in-the-loop (HIL) test bench for the validation of production transmission controls software, with a focus on a closed-loop vehicle drive-train model incorporating a detailed automatic transmission plant dynamics model developed for certain applications. Specifically, this paper presents the closed-loop integration of a 6-speed automatic transmission model developed for our HIL transmission controller and algorithm test bench (Opal-RT TestDrive based). The model validation, integration and its application in an HIL test environment are described in details.

In a CAS system, the distance and relative velocity between front and host vehicles are estimated to calculate time-to-collision (TTC). The distance estimates by different methods will certainly include noise which should be removed to ensure the accuracy of TTC calculations. Kalman filter is a good tool to filter such type of noise. Nevertheless, Kalman filter is a model based filter, which means a correct model is important to get the good filtering results. Usually, a vehicle is either moving with a constant velocity (CV) or constant acceleration (CA) maneuvers. This means the distance data between front and host vehicles can be described by either constant velocity or constant acceleration model. In this paper, first, CV and CA models are used to design two Kalman filters and an interacting multiple model (IMM) is used to dynamically combine the outputs from two filters.

The need for improved emissions control in lean exhaust to meet tightening, world-wide NOx emissions standards has led to the development of selective catalytic reduction of NOx with ammonia as a major technology for emissions control. Current systems are being designed to use a solution of urea (32.5 wt %) dissolved in water or Diesel Exhaust Fluid (DEF) as the ammonia source. While DEF or AdBlue® is widely used as a source of ammonia, it has a number of issues at low temperatures, including freezing below −12 °C, solid deposit formation in the exhaust, and difficulties in dosing at exhaust temperatures below 200 °C. Additionally creating a uniform ammonia concentration can be problematic, complicating exhaust packaging and usually requiring a discrete mixer.

This paper presents the development of a transmission closed loop pressure control system. The objective of this system is to improve transmission pressure control accuracy by employing closed-loop technology. The control system design includes both feed forward and feedback control. The feed forward control algorithm continuously learns solenoid P-I characteristics. The closed loop feedback control has a conventional PID control with multi-level gain selections for each control channel, as well as different operating points. To further improve the system performance, Robust Optimization is carried out to determine the optimal set of control parameters and controller hardware design factors. The optimized design is verified via an L18 experiment on spin dynamometer. The design is also tested on vehicle.

Both Crash-Avoidance and Pre-Crash active safety technologies are being developed to help reduce the number of crashes and minimize the severity of crashes. The root basis in the development of new and improved active safety technologies always begins with gaining further knowledge about crash kinds and causes. The dynamics of crashes are quite complex. The evolving precursor crash situation initiated in the Crash-Avoidance time-period will vary from the imminent crash situation in the Pre-Crash time-period. As such, in order to develop the appropriate requirements for both crash-avoidance and pre-crash technologies, they must be analyzed from their respective crash data. A data-driven methodology process has been developed which partitions the field data with a perspective to crash-avoidance and pre-crash.

The paper describes a new strategy for real-time sensor diagnostics that is based on the statistical correlation of various sensor signal pairs. During normal fault-free operation there is a certain correlation between the sensor signals which is lost in the event of a fault. The proposed algorithm quantifies the correlation between sensor signal pairs using real-time scalar metrics based on the Mahalanobis-distance concept. During normal operation all metrics follow a similar pattern, however in the event of a fault; metrics involving the faulty sensor would increase in proportion to the magnitude of the fault. Thus, by monitoring this pattern and using a suitable fault-signature table it is possible to isolate the faulty sensor in real-time. Preliminary simulation results suggest that the strategy can mitigate the false-alarms experienced by most model-based diagnostic algorithms due to an intrinsic ability to distinguish nonlinear vehicle behavior from actual sensor faults.

During the production controller and software development process, one critical step is the controller and software verification. There are various ways to perform this verification. One of the commonly used methods is to utilize an HIL (hardware-in-the-loop) test bench to emulate powertrain hardware for development and validation of powertrain controllers and software. A key piece of an HIL bench is the plant dynamics model used to emulate the external environment of a modern controller, such as engine (ECM), transmission (TCM) or powertrain controller (PCM), so that the algorithms and their software implementation can be exercised to confirm the desired results. This paper presents a 6-speed automatic transmission plant dynamics model development for hardware-in-the-loop (HIL) test bench for the validation of production transmission controls software. The modeling method, model validation, and application in an HIL test environment are described in details.

Production software validation is critical during software development, allowing potential quality issues that could occur in the field to be minimized. By developing automated and repeatable software test methods, test cases can be created to validate targeted areas of the control software for confirmation of the expected results from software release to release. This is especially important when algorithm/software development timing is aggressive and the management of development activities in a global work environment requires high quality, and timely test results. This paper presents a hardware-in-the-loop (HIL) test bench for the validation of production transmission controls software. The powertrain model used within the HIL consists of an engine model and a detailed automatic transmission dynamics model. The model runs in an OPAL-RT TestDrive based HIL system.

This paper describes a new tool to capture cylinder pressure information, calculate combustion parameters, and implement control algorithms. There are numerous instrumentation and prototyping systems which can provide some or all of this capability. The Cylinder Pressure Development Controller (CPDC) is unique in that it uses advanced high volume automotive grade circuitry, packaging, and software methodologies. This approach provides insight regarding the implementation of cylinder pressure based controls in a production engine management system. A high performance data acquisition system is described along with a data reduction technique to minimize data processing requirements. The CPDC software architecture is discussed along with model-based algorithm development and autocoding. Finally, CPDC calculated combustion parameters are compared with those from a well established combustion analysis system and thermodynamic simulations.

Computer simulation was used as a complement to crash and injury field data analysis and physical sled and barrier tests to investigate and predict the spinal injuries of a rear impact in an IndyCar. The model was expected to relate the spinal loads to the observed injuries, thereby predicting the probability and location of spinal fractures. The final goal is to help reduce the fracture risk by optimizing the seat and restraint system design and the driver's position using computer modeling and sled testing. MADYMO Full FE Human Body Model (HBM) was selected for use because of its full spinal structural details and its compatibility with the vehicle and restraint system models. However, the IndyCar application imposed unique challenges to the HBM. First, the driver position in a race car is very different from that in a typical passenger car.

Robust Engineering techniques developed by Taguchi have traditionally applied to the optimization of engineering designs. Robust Engineering methods also may be applied to software testing of ECU algorithms. The net result is an approach capable of improving the software algorithm in one of two ways. First the approach can identify the range of areas which prove problematic to the software such that a robust solution may be developed. Conversely, the approach can be used as a general strategy to verify that the software is robust over the range of inputs tested. The robust engineering methods applied to software testing utilize orthogonal array experiments to test software over a range of inputs. The actual software trials are best performed in the simulation environment and also via automated test hardware in the loop configurations in realtime. This paper outlines a process for applying Robust Engineering methods to software testing.

A new optimal control strategy for dealing with braking actuator failures in a vehicle equipped with a brake-by-wire and steer-by- wire system is described. The main objective of the control algorithm during the failure mode is to redistribute the control tasks to the functioning actuators, so that the vehicle performance remains as close as possible to the desired performance in spite of a failure. The desired motion of the vehicle in the yaw plane is determined using driver steering and braking inputs along with vehicle speed. For the purpose of synthesizing the control algorithm, a non-linear vehicle model is developed, which describes the vehicle dynamics in the yaw plane in both linear and non-linear ranges of handling. A control allocation algorithm determines the control inputs that minimize the difference between the desired and actual vehicle motions, while satisfying all actuator constraints.

In this paper a method of mitigating the consequences of potential brake actuator failure in vehicles with brake-by-wire (BBW) and possibly with steer-by-wire (SBW) systems is described. The proposed control algorithm is based on rules derived from general principles of vehicle dynamics. When a failure of one actuator is detected, the algorithm redistributes the braking forces among the remaining actuators in such a way that the desired deceleration of vehicle is followed as closely as possible, while the magnitude and the rate of change of the yaw moment caused by asymmetric braking are properly managed. When vehicle is equipped with BBW system only, or when the desired deceleration can be obtained by redistributing of braking forces, without generating an undesired yaw moment, no steering correction is used. Otherwise, a combination of brake force redistribution and steering correction (to counter the yaw moment generated by non-symmetric braking) is applied.

Electro-mechanical brakes (EMBs) are emerging as a new approach to enhance brake system features as well as braking performance. This paper takes a fresh look at the switched reluctance (SR) drive as a possible prime mover technology for EMB applications. The switched reluctance motor has attractive potential, in view of its robustness, dynamic bandwidth and fault tolerance. An overall assessment of the approach is made based on bench performance of a prototype EMB caliper with an SR drive executing typical braking patterns. It is shown that the SR motor can provide the required overall brake actuator performance. Various implementation options are examined to lower cost, with particular focus on electronic design, control algorithms and motor position sensing.

In occupant sensing system development, the Anthropomorphic Test Dummy (ATD) and the Occupant Classification ATD (OCATD) are frequently used to simulate live human subjects in the testing and validation of weight based occupant sensing systems. A study was conducted to investigate the range of loading differences between these ATDs and live human subjects over various seating postures and conditions. The results of the study revealed that differences in seat load patterns could be significant, even though both the ATD and live humans are in the same weight and body size categories. Seat loading was measured using Hybrid III (5th percentile female, 50th percentile male, and 3 year old) ATDs, OCATDs (OCATD5 - 5th percentile female, and OCATD6 - 6 yr old child), and a CRABI (12-month old) dummy. Human subjects in the same weight and height categories as the above listed ATDs were also measured.

This study examines the effectiveness of gaseous oxygen at preventing embrittlement in steel associated with exposure to gaseous hydrogen under static loading conditions. Notched C-ring samples machined from 4340 steel and heat treated to HRC 51-53 were used to test the neutrality of an oxygen-hydrogen gas mixture similar to that which may be used as a generant in an air bag inflator. The 29 percent oxygen to hydrogen gas ratio of the gas mixture was found to be sufficient to protect the steel from hydrogen embrittlement under static loading conditions. This would indicate that any steel with a hardness of HRC 51 or lower would be safe to use in gas-based air bag inflators containing a oxygen to hydrogen gas ratio of 29 percent or higher.

Embedded controllers and digital signal processors are increasingly being used in automotive safety critical control systems. Controller integrity is a significant concern in these systems. Over the past decade, several techniques have been published about controller safety and integrity verification. These techniques include: single processor with watchdog, dual processors, dual core processor, and asymmetric processor (intelligent watchdog). Each of these techniques have benefits, however, many new non-distributed safety-critical systems are applying the asymmetric processor technique to help verify controller integrity. This paper discusses an overview of five controller integrity techniques, and then provides a detailed discussion of an asymmetric processor approach. This paper presents two different options within the asymmetric processor approach.