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This study proposes a new algorithm that can render a realistic image of an automotive rear lamp using the backward ray tracing method. To produce a realistic image similar to that perceived by the human eye, the physical transformation procedures of light energy are traced by a spectral interaction definition. The incident light energy at the eye point estimated by a ray tracing algorithm is represented by XYZ tri-stimulus values, which are then converted into RGB values considering the particular display device. A more effective form of light source modeling than the Monte-Carlo integration method is also applied for accurate simulation. Finally, comparisons of traced results and real measurements are performed in terms of the spectral distribution, image detail, and visual experiments.

This paper describes a reference steering feel tracking algorithm for Electric-Power-Steering (EPS) system. Development of the EPS system with intended steering feel has been time-consuming procedure, because the feedforward map-based method has been applied to the conventional EPS system. However, in this study, a three-dimensional reference steering feel surface, which is determined from current vehicle states, is proposed. In order to track the proposed reference steering feel surface, sliding mode approach is applied to second-order steering dynamics model considering a coulomb friction model. An adaptive technique is utilized for robustness against uncertainties. In order to validate the proposed EPS control algorithm, hardware-in-the-loop simulation (HILS) has been conducted with respect to a typical steering test. It is shown that the reference steering feel is realized well by the proposed EPS control algorithm.

Electrical system capacity determination for conventional vehicles can be expensive due to repetitive empirical vehicle-level testing. Electrical system modeling and simulation have been proposed to reduce the amount of physical testing necessary for component selection [1, 2]. To add value to electrical system component selection, the electrical system simulation models must regard the electrical system as a whole [1]. Electrical system simulations are heavily dependent on the battery sub-model, which is the most complex component to simulate. Methods for modeling the battery are typically unclear, difficult, time consuming, and expensive. A simple, fast, and effective equivalent circuit model structure for lead-acid batteries was implemented to facilitate the battery model part of the system model. The equivalent circuit model has been described in detail. Additionally, tools and processes for estimating the battery parameters from laboratory data were implemented.

The growing concern surrounding Sports Utility Vehicle (SUV) rollover incidences and their consequences have prompted to investigate the sensitivity of critical vehicle parameters on rollover. In this paper, dynamic rollover simulation of Sports Utility Vehicles is carried out using a validated nonlinear vehicle model in Matlab/Simulink. A standard model is considered and critical vehicle parameters like CG height, track width and wheel base are varied within chosen specified limits to study its influence on roll behavior during Fishhook steering maneuver. A roll stability criterion based on two wheel lift off phenomenon is adopted for rollover propensity prediction. Further dynamic rollover characteristics of the vehicle are correlated with Static Stability Factor (SSF), Roll Stability Factor (RSF) and Two Wheel Lift off Velocity (TWLV).

Commercial vehicle manufacturers face unique challenges for the development of vehicle electronics systems. For one, customers typically have unique requirements coupled with an expectation of high reliability. Vehicle electronics is often the enabler for customized features. Ensuring that the vehicle will perform as demanded and promised adds a degree of burden on the vehicle manufacturers. Furthermore, the verification and testing of a large number of unique electronic system configurations is very expensive and time-consuming. This paper will explore how Model-Based Design can be used to meet these challenges and provide a high degree of confidence for both the manufacturer and the customer that requirements have been met. It will discuss factors to consider to support configurability, approaches for defining a system architecture that facilitates reuse, and capabilities for modeling state-based systems.

Using Model-Based Design, engineers model complex systems and simulate them on their desktop environment for analysis and design purposes. Model-Based Design supports a wide variety of C/C++ code generation applications that include stand-alone simulation, rapid control prototyping, hardware-in-the-loop testing, and production or embedded code deployment. Many of these code generation scenarios impose different requirements on the generated code. Stand-alone simulations usually need to run fast, for parameter sweep or Monte Carlo studies, but do not need to execute in true hard real-time. Hardware-in-the-loop tests by definition use engine control unit (ECU) component hardware that requires a hard real-time execution environment to protect the physical devices. Code generated for production ECUs must satisfy hard real-time, efficiency, legacy code, and other requirements involving verification and validation efforts.

Automatic code generation from models is actively used at Caterpillar for powertrain and machine control development. This technology was needed to satisfy the industry's demands for both increased software feature content, and its added complexity, and a short turn-around time. A pilot development effort was employed initially to roll out this new technology and shape the deployment strategy. As a result of a series of successful projects involving rapid prototyping and production code generation, Caterpillar will deploy MathWorks modeling and code generation products as their department-wide production development capability. The data collected indicated a reduction of person hours by a factor of 2 to 4 depending on the project and a reduction of calendar time by a factor of greater than 2. This paper discusses the challenges, results, and lessons learned, during this pilot effort from the perspectives of both Caterpillar and The MathWorks.

Model-Based Design is increasingly prevalent in industrial sectors including aerospace and automotive, but lacking from college and university curricula. The need for students to be adept at the modeling of systems, their associated subsystems, and overall system controller as per the standard industry practice is the impetus for The MathWorks, Freescale, and MotoTron to partner with Rose-Hulman Institute of Technology to address the lack of students familiar with this industry standard practice. Rose-Hulman Institute of Technology has created the Model-Based-System Design Center with the express purpose of introducing the philosophy of Model-Based Design to the educational community. This paper describes the function of the Center and the teaching materials currently being generated.

This paper proposes a torque tracking algorithm via steer by wire to achieve the target steering feel and proposed a modified friction model to obtain return-ability. A three dimensional reference steering wheel torque map is designed using the measurement data of the steering characteristics of the target vehicle at a transition test and a weave test. In order to track the reference steering wheel torque, a sliding mode control is used in the tracking algorithm. In addition, to achieve return-ability, the modified friction model for steer by wire is used instead of the friction model defined in the reference steering wheel torque map. The modified friction model is composed of various models according to the angular velocity. The angular velocity and the angular acceleration used in the control algorithm are estimated using a kalman filter.

This paper presents the business purpose, software architecture, technology integration, and applications of the Cummins Vehicle Mission Simulation (VMS) software. VMS is the value-based analysis tool used by the marketing, sales, and product engineering functions to simulate vehicle missions quickly and to gauge, communicate, and improve the value proposition of Cummins engines to customers. VMS leverages the best of software architecture practices and proven technologies available today. It consists of a close integration of MATLAB and Simulink with Java, XML, and JDBC technologies. This Windows compatible application software uses stand-alone mathematical models compiled using Real Time Workshop. A built-in MySQL database contains product data for engines, driveline components, vehicles, and topographic routes. This paper outlines the database governance model that facilitates effective management, control, and distribution of engine and vehicle data across the enterprise.

When developing production software for fixed-point Engine Control Units (ECUs), it is important to consider the transition from floating-point to fixed-point algorithms. Systems engineers frequently design algorithms in floating-point math, usually double precision. This represents the ideal algorithm behavior without much concern for its final realization in production software and hardware. Software engineers and suppliers in mass production environments, however, are concerned with production realities and often need to convert these algorithms to fixed-point math for their integer-only hardware. A key task is to design scale factors that maximize code efficiency by minimizing the bytes used, while also minimizing quantization effects such that the fixed-point algorithms match the floating-point results within an acceptable numerical margin.

Modern electronic control units (ECUs) are increasingly being developed using Model-Based Design with production code generation. With this approach, systems and software engineers model and simulate algorithms using block diagrams, state machines and data dictionaries. Code is then automatically generated from these models and placed into rapid prototyping or production microprocessors. The model structure and code generation configuration options significantly impact the efficiency and clarity of the design and resulting code. While clarity and efficiency may not be much of an issue when performing initial rapid prototyping evaluations on high performance computers, it is a significant concern in formal software development processes targeting low-cost, low-performance mass production ECUs. This paper describes model style guidelines and the best practices for automatically designing and generating optimized fixed-point and floating-point code.

In this paper, we show how Model-Based Design can be applied in the development of a hybrid electric vehicle system. The paper explains how Model-Based Design begins with defining the design requirements that can be traced throughout the development process. This leads to the development of component models of the physical system, such as the power distribution system and mechanical driveline. We also show the development of an energy management strategy for several modes of operation including the full electric, hybrid, and combustion engine modes. Finally, we show how an integrated environment facilitates the combination of various subsystems and enables engineers to verify that overall performance meets the desired requirements.

The increased adoption of electronic controls in off-highway machines increases the complexity of typical machine systems and stresses the traditional process used to develop these machines. To address this issue design engineers are turning from the traditional design methods to Model-Based Design. By using models in the early design stages, engineers can create executable specifications that enable them to immediately validate and verify specifications against the requirements. These models also allow the machine designer to evaluate the complex interactions between mechanics, hydraulics, electronics and other physical phenomena and thereby detect design errors earlier when the cost to fix them is less. This paper presents a model-based approach for developing off-highway equipment machine systems. A dynamic model of the machine and the electro-hydraulic implement and propulsion system is developed and used to verify the overall machine behavior.

The need to meet new regulatory requirements as well as customer expectations in terms of machine productivity, safety, maintenance and uptime, is driving a significant transformation from conventional hydraulic and mechanical systems to electro-hydraulic systems in the earth-moving and agricultural equipment industry. The ability to model and simulate such systems plays a key role in this transformation by allowing manufacturers to test whether the system meets requirements using virtual prototypes rather than physical prototypes. Modeling the electrical, electronic, mechanical, and hydraulic domains in the same modeling environment can significantly improve the product development process of such machines. This paper illustrates those benefits using the example of an electro-hydraulic implement system.

In response to marketplace demand for increased engine performance and economy, spark-ignition (SI) engine applications with dual-independent variable cam-phaser actuators (DIVCP) are now commonplace. In this paper, the minimum number of test measurements required to optimally calibrate the steady-state spark advance and cam-phaser settings of a SI DIVCP engine was determined, using a high-fidelity model of a 2.2L SI DIVCP engine with predictive combustion capability as a basis. A calibration development process was designed to objectively determine the minimum number of torque vs. spark advance sweeps required for the SI DIVCP engine. First, Torque production results from calibration tables based on cost-feasible sets of 52, 96, 173, 250, 329, and 406 sweeps were determined. Next, calibration reference tables were developed from an exhaustive data collection process based on 10,000 sweeps.

Typically, battery models are complex and difficult to parameterize to match real-world data. Achieving a good generalized fit between measured and simulated results should be done using a variety of laboratory data. Numerical optimizations can ensure the best possible fit between a simulation model and measured data, given a set of constraints. In this paper, we propose a semi-automated process for parameterizing a lithium polymer battery (LiPB) cell simulation model that is able to satisfy constraints on the optimized parameters. This process uses a number of measured data sets under a variety of conditions. An iterative numerical optimization algorithm using Simulink Parameter Estimation was implemented to estimate parameter values by minimizing error between measured and simulated results.

The chemical storage battery is currently the primary choice of automotive powertrain designers for hybrid-electric vehicles. This design suffers from complexity, manufacturing, cost, durability, poor performance predictability and other problems. Additionally, the trend in hybrid powertrain design is to move from high energy density to high power density. A proposed alternative to chemical batteries for some hybrid vehicle applications is an electro-mechanical battery (EMB) that combines an electric machine with hydro-pneumatics to provide energy capture, storage, and propulsion assistance. An initial multi-domain physical system model of an EMB-based hybrid powertrain has been developed in the Simulink environment to show the behavior of the EMB design in a midsize hybrid passenger vehicle application.

Software developed for safety-critical systems needs to be of high integrity. Special precautions and development steps are needed for high-integrity software that are not required for other software, although many would argue that they should be. Examples include language subsets, Verification and Validation (V&V), inspections, requirements traceability, documentation, and structural test coverage. Production code generation supports these activities by providing a complete software engineering development environment using models to specify the software. The models can then be tested and stressed within boundaries of the modeling environment. The tests and results can then be reused and applied to the generated code. This paper describes high-integrity code development techniques and shows how they can be automated and applied at the model level, improving quality while shortening design cycles.

Model-guided development of drivetrain control and calibration is a key enabler of robust and efficient vehicle design process. A number of CAE tools are available today for modeling hydro-mechanical systems. Automatic transmission behaviors are well understood to effectively tune the model parameters for targeted applications. Drivetrain models provide physical insight for understanding the effects of component interactions on system behaviors. They are also widely used in HIL/SIL environments to debug control strategies. Nonetheless, it is still a challenge to predict shift quality, especially during a sequence of multiple events, with enough accuracy to support model-guided control design and calibration. The inclusion of hydraulic circuits in simulation models often results in challenges for numerical simulation.