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As the new features for driver assistance and active safety systems are growing rapidly in vehicles, the simulation within a virtual environment has become a necessity. The current active safety system consists of Electronic Control Units (ECUs) which are coupled to camera and radar sensors. Two methods of implementation exists, integrated sensors with control modules or separation of sensors form control modules. The subsystem integration testing poses new challenges for virtual environment for simulation of active safety features. The comprehensive simulation environment for integration testing consists of chassis controls, powertrain, driver assistance, body and displays controllers. Additional complexity in the system is the serial communication strategy. Multiple communication protocols such as GMLAN, LIN, standard CAN, and Flexray could be present within the same vehicle topology.

General Motors' (GM) eAssist powertrain builds upon the knowledge and experience gained from GM's first generation 36Volt Belt-Alternator-Starter (BAS) system introduced on the Saturn VUE Green Line in 2006. Extensive architectural trade studies were conducted to define the eAssist system. The resulting architecture delivers approximately three times the peak electric boost and regenerative braking capability of 36V BAS. Key elements include a water-cooled induction motor/generator (MG), an accessory drive with a coupled dual tensioner system, air cooled power electronics integrated with a 115V lithium-ion battery pack, a direct-injection 2.4 liter 4-cylinder gasoline engine, and a modified 6-speed automatic transmission. The torque-based control system of the eAssist powertrain was designed to be fully integrated with GM's corporate common electrical and controls architectures, enabling the potential for broad application across GM's global product portfolio.

This paper analyzes the control of the series-parallel powersplit used in the 2001 Michigan Tech FutureTruck. An electronic throttle controller is implemented and a new control algorithm is proposed and tested. A vehicle simulation has been created in MATLAB and the control algorithm implemented within the simulation. A program written in C has also been created that implements the control algorithm in the test vehicle. The results from both the simulation and test vehicle are presented and discussed and show a 15% increase in fuel economy. With the increase in fuel economy, and through the use of the original exhaust after treatment, lower emissions are also expected.

This paper describes an environment for the development of production Engine Management Systems (EMS). This includes a formal framework and modeling methodology. The environment is based on using Simulink/Stateflow for developing a control system executable specification and a plant model. This allows for simulations of the system to be performed at the engineer's desk, which is identical performance with production software. We provide the details for incorporating production legacy code into the Simulink/Stateflow control system. The system includes a multi-rate, and event driven operating system. This system is developed to facilitate new algorithm development and automated software testing. Based on Simulink/Stateflow this specification will be suitable for use with commercial automatic code generation tools.

This work examines the development and implementation of a pulsing brake control system as part of a Forward Collision Warning (FCW) System for an Adaptive Cruise Control (ACC) prototype vehicle. The brake pulse is a likely candidate to be employed with visual and auditory cues in the event of an imminent collision alert level when the driver is not in ACC mode.

Delphi is developing a new combustion technology called Gasoline Direct-injection Compression Ignition (GDCI), which has shown promise for substantially improving fuel economy. This new technology is able to reuse some of the controls common to traditional spark ignition (SI) engines; however, it also requires several new sensors and actuators, some of which are not common to traditional SI engines. Since this is new technology development, the required hardware set has continued to evolve over the course of the project. In order to support this development work, a highly capable and flexible electronic control system is necessary. Integrating all of the necessary functions into a single controller, or two, would require significant up-front controller hardware development, and would limit the adaptability of the electronic controls to the evolving requirements for GDCI.

Recent trends in the automotive industry show growing demands for the introduction of new in-vehicle features (e.g., smart-phone integration, adaptive cruise control, etc.) at increasing rates and with reduced time-to-market. New technological developments (e.g., in-vehicle Ethernet, multi-core technologies, AUTOSAR standardized software architectures, smart video and radar sensors, etc.) provide opportunities as well as challenges to automotive designers for introducing and implementing new features at lower costs, and with increased safety and security. As a result, the design of Electrical/Electronic (E/E) architectures is becoming increasingly challenging as several hardware resources are needed. In our earlier work, we have provided top-level definitions for three relevant metrics that can be used to evaluate E/E architecture alternatives in the early stages of the design process: flexibility, scalability and expandability.

GM has recently developed two kinds of vehicle electrification architectures. First is VOLTec, a heavy electrification architecture, and second is eAssist, a light electrification architecture. An overview, of IGBT power modules & inverters used in VOLTec and eAssist, is presented. Alternative power modules from few cooperative suppliers are also described in a benchmarking study using key metrics. Inverter test set up, procedure and instrumentation used in GM Power Electronics Development Lab, Milford are described. GM electrification journey depends on Power Electronics lab' passive test benches; double pulse tester, inductive resistive load bench and active emulator test cell without electric machines. Such test benches are preferred before dyne test cells are used for inverter software/hardware integration and motor durability tests cycles. Specific test results are presented.

The effects of using blended renewable diesel fuel (30% vol.), obtained from Rapeseed Methyl Ester (RME) and Hydrotreated Vegetable Oil (HVO), in a Euro 5 small displacement passenger car diesel engine have been evaluated in this paper. The hydraulic behavior of the common rail injection system was verified in terms of injected volume and injection rate with both RME and HVO blends fuelling in comparison with commercial diesel. Further, the spray obtained with RME B30 was analyzed and compared with diesel in terms of global shape and penetration, to investigate the potential differences in the air-fuel mixing process. Then, the impact of a biofuel blend usage on engine performance at full load was first analyzed, adopting the same reference calibration for all the tested fuels.

Today many vehicles are being developed with advanced computing and sensing technologies. These new technologies have contributed in enhancing driving safety and convenience. As an example, the Adaptive Cruise Control (ACC) can automatically adjust the vehicle speed to driver's set speed and maintain the driver-requested headway distance to the lead vehicle. In this paper, we further consider the automatic control of speed according to the road attributes, e.g., the speed limit and curve of the road. Two new features, ‘speed limit follower’ and ‘curve speed control’ algorithms, are proposed in this paper. These new features communicate with the conventional ACC system and control the vehicle speed while traveling across different curved roads and speed limit zones. These new features were developed as an independent function, so they can be integrated with any other existing ACC systems.

Today's advanced technology engines have a high content of electronic actuation requiring sophisticated real-time embedded software sensing and control. To enable research on such engines, a system with a flexible engine control unit (ECU) that can be rapidly configured and programmed is desired. Such a system is being used in the Advanced Internal Combustion Engine (AICE) Laboratories at Michigan Tech University (MTU) for research on a multi-cylinder spark-ignited gasoline, a high pressure common rail diesel and a single cylinder alternative fuels research engine. The system combines a production ECU with a software development system utilizing Mathworks Simulink/Stateflow © modeling tools. The interface in the Simulink modeling environment includes a library of modeling and interface blocks to the production Operating System (OS), Low Level Drivers (LLD) and CAN-based calibration tool.

An air suspension system can consist of many different components. These components include an air compressor, air springs, pneumatic solenoid valves, height sensors, electronic control unit, air reservoir, air lines, pressure sensor, temperature sensor, etc. The system could be designed as a 2-corner rear air suspension or a 4-corner air suspension. In this paper, the pneumatic models of air suspension systems are presented. The suspension system models are implemented in AmeSim. The suspension controls are implemented using Matlab/Simulink. The compressor was modeled using the standard AmeSim element with known mass flow rate as a function of pressure ratio. Air lines were modeled using a friction submodel of pneumatic pipe and control (isolation) valves are modeled using 2 position, 2 port pneumatic servo valves. The air spring is modeled as a single pneumatic chamber, single rod jack with spring assistance to account for spring nonlinearities.

Since the late 1980s, Delphi Automotive Systems has been very involved with the practical development of a variety of Collision Avoidance products for the near- and long-term automotive market. Many of these complex collision avoidance products will require the integration of various vehicular components/systems in order to provide a cohesive functioning product that is seamlessly integrated into the vehicle infrastructure. One such example of this system integration process was the development of an Adaptive Cruise Control system on an Opel Vectra. The design approach heavily incorporated system engineering processes/procedures. The critical issues and other technical challenges in developing these systems will be explored. Details on the hardware and algorithms developed for this vehicle, as well as the greater systems integration issues that arose during its development will also be presented.

Today, electrical/electronic systems like ABS/power brakes and electric power steering are all designed to enhance, not replace a mechanical function. If an electrical or electronic fault occurs, the function reverts to the base mechanical capability. Future E/E systems, such as steer-by-wire and brake-by- wire replace mechanical linkages with electrical or optical signals as in computer networks. While these systems offer many potential safety benefits, they will require different strategies for dependability, and as with any vehicle system, they will further require that dependability be an integral part of the overall E/E system design. This paper illustrates how by-wire systems drive different dependability requirements and discusses some key technologies that are emerging to meet these requirements.

Delphi has developed a second-generation Electronic Throttle Control system optimized for high volume applications. The Delphi system integrates several unique driver performance features, extensive security/diagnostics, and provides significant benefits for the vehicle manufacturer. For Model Year 2000, the Delphi ETC system has been successfully implemented on several popular SUVs and passenger cars built and sold around the world. The ETC driver features, security systems, and manufacturer benefits are presented as implemented on these Model Year 2000 applications.

This paper presents the development of a reduced-order powertrain model for energy and SOC estimation of a multi-mode plug-in hybrid electric vehicle using only vehicle speed profile and route elevation as inputs. Such a model is intended to overcome the computational inefficiencies of higher fidelity powertrain and vehicle models in short and long horizon energy optimization efforts such as Coordinated Adaptive Cruise Control (CACC), Eco Approach and Departure (EcoAND), Eco Routing, and PHEV mode blending. The reduced-order powertrain model enables Connected and Automated Vehicles (CAVs) to utilize the onboard sensor and connected data to quickly react and plan their maneuvers to highly dynamic road conditions with minimal computational resources.

The Electronic Control Unit (ECU) of an Electric Power Steering (EPS) system is a core device to decide how much assistance an electric motor applies on a steering wheel. The EPS ECU plays an important role in EPS systems. The effectiveness of an ECU needs to be thoroughly tested before mass production. Hardware-in-the-loop simulation provides an efficient way for the development and testing of embedded controllers. This paper focuses on the development of a HiL system for testing EPS controllers. The hardware of the HiL system employs a dSPACE HiL simulator. The EPS plant model is an integrated model consisting of a Vehicle Dynamics model of the dSPACE Automotive Simulation Model (ASM) and the Nexteer Steering model. The paper presents the design of an EPS HiL system, the simulation of sensors and actuators, the functions of the ASM Vehicle Dynamics model, and the integration method of the ASM Vehicle Dynamics model with a Steering model.

RACam [1] is an Active Safety product designed and manufactured at Delphi and is part of their ADAS portfolio. It combines two sensors - Electronically Scanned RADAR and Camera in a single package. RADAR and Vision fusion data is used to realize safety critical systems such as Adaptive Cruise Control (ACC), Autonomous Emergency Braking (AEB), Lane Departure Warning (LDW), Lane Keep Assist (LKA), Traffic Sign Recognition (TSR) and Automatic Headlight Control (AHL). Figure 1 RACam Front View. With an increase in Active Safety features in the automotive market there is also a corresponding increase in the complexity of the hardware which supports these safety features. Delphi’s hardware design for Active Safety has evolved over the years. In Delphi’s RACam product there are a number of critical components required in order to realize RADAR and Vision in a single package. RACam is also equipped with a fan and heater to improve the operating temperature range.

The proliferation of small silicon micro-chips has led to a large assortment of low-cost transducers for data acquisition. Production vehicles on average exploit more than 60 on board sensors, and that number is projected to increase beyond 200 per vehicle by 2020. Such a large increase in sensors is leading the fourth industrial revolution of connectivity and autonomy. One major downfall to installing many sensors is compromises in their accuracy and processing power due to cost limitations for high volume production. The same common errors in data acquisition such as sampling, quantization, and multiplexing on the CAN bus must be accounted for when utilizing an entire array of vehicle sensors. A huge advantage of onboard sensors is the ability to calculate vehicle parameters during a daily drive cycle to update ECU calibration factors in real time. One such parameter is driveline damping, which changes with gear state and drive mode. A damping value is desired for every gear state.

This paper describes a semi-active damping control system that responds in real-time to road and driving conditions based on body motions as determined through ABS wheel speed sensors. The use of these existing sensors for vehicle information eliminates the need for the additional sensors (e.g. accelerometers and body-to-wheel position/velocity sensors) that are commonly part of semi-active suspension systems. This technology also allows for further cost and part count reductions through the combination of the suspension and brake controls into a single electronic control unit. This paper has been previously presented in 1998 at the SAE Controlled Suspension System Toptec.