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The Chevrolet Volt is an electric vehicle with extended-range that is capable of operation on battery power alone, and on engine power after depletion of the battery charge. First generation Chevrolet Volts were driven over half a billion miles in North America from October 2013 through September 2014, 74% of which were all-electric [1, 12]. For 2016, GM has developed the second-generation of the Volt vehicle and “Voltec” propulsion system. By significantly re-engineering the traction power inverter module (TPIM) for the second-generation Chevrolet Volt extended-range electric vehicle (EREV), we were able to meet all performance targets while maintaining extremely high reliability and environmental robustness. The power switch was re-designed to achieve efficiency targets and meet thermal challenges. A novel cooling approach enables high power density while maintaining a very high overall conversion efficiency.

The auto industry has had decades of experience with designing safe vehicles. The introduction of highly integrated features brings new challenges that require innovative adaptations of existing safety methodologies and perhaps even some completely new concepts. In this paper, we describe some of the new challenges that will be faced by all OEMs and suppliers. We also describe a set of generic top-level potential hazards that can be used as a starting point for the Preliminary Hazard Analysis (PHA) of a vehicle software-intensive motion control system. Based on our experience with the safety analysis of a system of this kind, we describe some general categories of hazard causes that are considered for software-intensive systems and can be used systematically in developing the PHA.

By adapting vehicle control systems to the skill level of the driver, the overall vehicle active safety provided to the driver can be further enhanced for the existing active vehicle controls, such as ABS, Traction Control, Vehicle Stability Enhancement Systems. As a follow-up to the feasibility study in [1], this paper provides some recent results on data-driven driving skill characterization. In particular, the paper presents an enhancement of discriminant features, the comparison of three different learning algorithms for recognizer design, and the performance enhancement with decision fusion. The paper concludes with the discussions of the experimental results and some of the future work.

Model-based design is a collection of practices in which a system model is at the center of the development process, from requirements definition and system design to implementation and testing. This approach provides a number of benefits such as reducing development time and cost, improving product quality, and generating a more reliable final product through the use of computer models for system verification and testing. Model-based design is particularly useful in automotive control applications where ease of calibration and reliability are critical parameters. A novel application of the model-based design approach is demonstrated by The Ohio State University (OSU) student team as part of the Challenge X advanced vehicle development competition. In 2008, the team participated in the final year of the competition with a highly refined hybrid-electric vehicle (HEV) that uses a through-the-road parallel architecture.

We start our study with a survey of existing variable valve actuation (VVA) devices. We then describe our work, taken place over a time period from 2001 to 2007, on several VVA concepts. All of our projects described include pre-design modeling and simulation. Also, for each one of the proposed designs, a bench-top motorized test fixture was built and ran for proof of concept. Our projects represent a mixture of exploratory research and production-related development work. They can be classified in four broad categories: discrete-step systems; mechanical continuously-variable systems; active stationary-hydraulic lash adjusters; cam-driven hydraulic-lost-motion mechanism. These devices differ in their complexity and versatility but offer a spectrum of design solutions applicable to a range of products. Specific attributes of these different approaches are analyzed and discussed, and some test results are presented.

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.

A key element of General Motors' Advanced Propulsion Technology Strategy is the electrification of the automobile. The objectives of this strategy are reduced fuel consumption, reduced emissions and increased energy security/diversification. The introduction of hybrid vehicles was one of the first steps as a result of this strategy. To determine future opportunities and direction, an extensive study was completed to better understand the ability of Plug-in Hybrid Electric Vehicles (PHEV) and Extended-Range Electric Vehicles (E-REV) to address societal challenges. The study evaluated real world representative driving datasets to understand actual vehicle usage. Vehicle simulations were conducted to evaluate the merits of PHEV and E-REV configurations. As derivatives of conventional full hybrids, PHEVs have the potential to deliver a significant reduction in petroleum usage.

Robust assessment using standardized signal-to-noise (SS/N) is a Design For Six Sigma (DFSS) methodology used to assess the mating quality of USCAR electrical connectors. When the insertion force vs. distance relationship is compared to a standard under varying environmental and system-related noise conditions, the ideal function is transformed into a linear relationship between actual and ideal force at the sample points acquired during the mating displacement. Since the ideal function used in the robust assessment of competing designs has a linear slope of 1 through the origin, the SS/N function used is of the form 10 log (1/σ2), also known as nominal-the-best type 2. Using this assessment methodology, designs are compared, with a higher SS/N indicating lower variation from the standard.

This paper presents the new techniques/methods being used for the rapid vehicle development and system level performance assessment. It consists of two parts: the first part presents the automated multilevel substructuring (AMLS) technique, which greatly reduces the computational demands of larger finite element models with millions of degrees of freedom(DOF) and extends the capabilities to higher frequencies and higher level of accuracy; the second part is on the superelement in conjunction with the Component Mode Synthesis (CMS) and also Automated Component Mode Synthesis (ACMS) techniques. In superelement, a full vehicle model is divided into components such as Body-in-white, Front cradle/chassis, Rear cradle/chassis, Exhaust, Engine, Transmission, Driveline, Front suspension, Rear suspension, Brake, Seats, Instrument panel, Steering system, tires, etc. with each piece represented by reduced stiffness, mass, and damping matrices.

Model-based design and development is emerging in the automotive industry, largely revealing its popularity in chassis control systems [1]. Although it is an efficient and accepted design tool for chassis systems, proper processes and strategies need to be in place to ensure the integrity and correctness of the production software. This paper describes software testing strategies for complex chassis control systems in a model-based environment. In detail, it highlights various testing methods for different phases, such as unit testing and integration testing. It will also address issues and challenges that were faced with each method and propose possible solutions.

This paper presents a comprehensive Matlab/Simulink-based framework that affords a rapid, systematic, and efficient engine control system development process including automated code generation. The proposed framework hinges on three essential pillars: 1 ) an accurate model for the target engine, 2) a toolset for systematic control design, and 3) a modular system architecture that enhances feature reusability and rapid algorithm deployment. The proposed framework promotes systematic model-based algorithm development and validation in virtual reality. Within this context, the framework affords integration and evaluation of the entire control system at an early development stage, seamless transitions across inherently incompatible product development stages, and rapid code generation for production target hardware.

The fierce competition and shifting consumer demands require automotive companies to be more efficient in all aspects of vehicle development and specifically in the area of embedded engine control system development. In order to reduce development cost, shorten time-to-market, and meet more stringent emission regulations without sacrificing quality, the increasingly complex control algorithms must be transportable and reusable. Within an efficient development process it is necessary that the algorithms can be seamlessly moved throughout different development stages and that they can be easily reused for different applications. In this paper, we propose a flexible engine control architecture that greatly boosts development efficiency.

Steer-by-wire systems (SBW) offer the potential to enhance steering functionality by enabling features such as automatic lane keeping, park assist, variable steer ratio, and advanced vehicle dynamics control. The lack of a steering intermediate shaft significantly enhances vehicle architectural flexibility. These potential benefits led GM to include steer-by-wire technology in its next generation fuel cell demonstration vehicle, called “Sequel.” The Sequel's steer-by-wire system consists of front and rear electromechanical actuators, a torque feedback emulator for the steering wheel, and a distributed electronic control system. Redundancy of sensors, actuators, controllers, and power allows the system to be fault-tolerant. Control is provided by multiple ECU's that are linked by a fault-tolerant communication system called FlexRay. In this paper, we describe the objectives for fault tolerance and performance that were established for the Sequel.

The hybrid system for the 2007 Model Year Saturn VUE Green Line Hybrid SUV was designed to provide the fuel economy of a compact sedan, while delivering improved acceleration performance over the base vehicle, and maintaining full vehicle utility. Key elements of the hybrid powertrain are a 2.4L DOHC engine with dual cam-phasers, a modified 4-speed automatic transmission, an electric motor-generator connected to the crankshaft through a bi-directional belt-drive system, power electronics to control the motor-generator, and a NiMH battery pack. The VUE's hybrid functionality includes: engine stop-start, regenerative braking, intelligent charge control of the hybrid battery, electric power assist, and electrically motored creep. Methods of improving urban and highway fuel economy via optimal use of the hybrid motor and battery, engine and transmission hardware and controls modifications, and vehicle enhancements, are discussed.

The Hood ajar sensing system provides customer feedback regarding the latch positional state of hood. If the sensing system is not robust to variation due to manufacturing, thermal conditions, and assembly, diagnostic failures can result. Executing various elements of the design for six sigma process can reduce the potential for diagnostic failures. This paper presents a method for achieving quality improvements by developing transfer functions, and using them for sensitivity and variance analysis. Control parameters were optimized to minimize non-conformal situations in the presence of various noise conditions.

Combustion feedback using cylinder pressure sensors, ion current sensors or alternative sensing techniques is actively under investigation by the automotive industry to meet future legislative emissions requirements. One of the drawbacks of many rapid prototyping engine management systems is their available analog interfaces, often limited to 10-12 bits with limited bandwidth, sampling rate and very simple anti-aliasing filters. Processing cylinder pressure or other combustion feedback sensors requires higher precision, wider bandwidths and more processing power than is typically available. For these reasons, Ricardo in collaboration with GM Research has developed a custom, high precision analog input subsystem for the rCube rapid prototyping control system that is specifically targeted at development of combustion feedback control systems.

The main objective of this paper was to determine if the vehicle performance can be maintained with a reduced mass cradle structure. Aluminum and magnesium cradles were compared with the baseline steel cradle. First, the steel chassis alone is analyzed with the refined finite element model and validated with experimental test data for the frequencies, normal modes, stiffnesses and the drive-point mobilities at various attachment mount/bushing locations. The superelement method in conjunction with the component mode synthesis (CMS) technique was used for each component of the vehicle such as Body-In-White, Instrument Panel, Steering Column Housing & Wheel, Seats, Cradles, CRFM, etc. After assemblage of all the superelements, analysis was carried out by changing the front and rear cradle gauges and the material properties. The drive-point mobility response was computed at various locations and the noise (sound pressure) level was calculated at the driver and passenger ears.

This paper presents a Power-Based Noise Reduction (PBNR) concept and uses PBNR to set vehicle acoustic specifications for sound package design. This paper starts with the PBNR definition and describes the correct measurement techniques. This paper also derives the asymptotic relationships among PBNR, conventional noise reduction (NR), and sound transmission loss, for a simple case consisting of the source, path, and receiver subsystems. The advantages of using PBNR over conventional Noise Reduction (NR) are finally demonstrated in vehicle measurement examples.

FlexRay is a new communication subsystem for future in-vehicle controls. There is a lack of mature model-based development methodologies to build complex FlexRay-based systems. In this paper we describe an end-to-end model-based development process for building a complex FlexRay-based distributed control system. We describe this in the context of safety critical x-by-wire systems for a realistic automotive application. This involves: control system modeling, functional simulation, and distributed software development. We first describe the process of functional and physical architecture design. Next we discuss the software development process dealing with software to hardware allocation, as well as scheduling of software and communication tasks on a time-triggered communication bus under stringent practical restrictions. We conclude by considering the integration issues relating to joint OEM/supplier development of distributed control systems.

A rapid prototyping controller (RPC) based, full-authority, diesel control system is developed, implemented, tested and validated on FTP cycle. As rapid prototyping controller, dSPACE Autobox is coupled with a fast processor based slave for lower level I/O control and a collection of in-house designed interface cards for signal conditioning. The base software set implemented mimics the current production code for a production diesel engine. This is done to facilitate realistic and accurate comparison of production algorithms with new control algorithms to be added on future products. The engine is equipped with all the state-of-the art subsystems found in a modern diesel engine (common rail fuel injection, EGR, Turbocharger etc.).