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The automotive industry is currently undergoing a significant transformation characterized by technological and commercial trends involving autonomous driving, connectivity, electrification, and shared service. Vehicles are becoming an integral part of a much broader ecosystem. In light of various new developments, the Software-Defined Vehicle (SDV) concept is gaining substantial attention and momentum. SDV emphasizes the central role of software in realizing and enhancing vehicle functions, enriching features, improving performance, adapting to surrounding environment and external conditions, customizing user experience, addressing changing customer needs, and enabling vehicles to dynamically evolve over their entire life cycle. The advancements in vehicle Electrical/Electronic (E/E) architecture and various key technologies serve as the technical foundation for the emergence of SDV.

With the ever-increasing requirements on vehicle performance, as well as the trend of vehicle becoming an integral part of a much bigger ecosystem involving automated driving, intelligent transportation and smart city, more and more electrical/electronic (E/E) systems are integrated in vehicles. Vehicle E/E architecture being the fundamental organization of E/E components, the relationship among the components and with the environment, as well as the principles guiding the design and evolution, has essential influences on vehicle E/E system functions and performance. This paper gives the definition of vehicle E/E architecture and provides different views. The guidelines, contents and process of E/E architecture design are discussed. The evolution of E/E architecture, influence of the latest technical trends including electrification, automated driving, and connectivity functions on E/E architecture, and how vehicle E/E architecture adapts to the technical trends are studied.

Ever increasing requirements for vehicle performance, fuel economy and emissions have been driving the development and adoption of various types of hybrid powertrains. There are many different configurations of hybrid powertrains, which may include such components as engine, generator and inverter, battery pack, ultracapacitor, traction motor and inverter, transmission, and various control units. A hardware-in-the loop (HiL) testing solution that is flexible enough to accommodate different types of hybrid powertrain configurations and run a range of test scenarios is needed to support on-going development activities in this field. This paper describes the design and implementation of such a HiL testing system. The system is centered on a high performance, real-time controller that runs powertrain, driveline, vehicle, and driver models.

Variable compression ratio and variable displacement technologies are adopted in internal combustion engines because these features provide further degrees of freedom to optimize engine performance for various operating conditions. This paper focuses on a multiple-link mechanism that realizes variable compression ratio and displacement by varying the piston motion, specifically the Top Dead Center (TDC) and Bottom Dead Center (BDC) positions relative to the crankshaft. It is determined that a major requirement for the design of this mechanism is when the control action changes monotonically over its whole range, the compression ratio and the displacement should change in opposite directions monotonically. This paper presents an approach on how to achieve multiple-link mechanism geometric designs that fulfill this requirement.

Due to growing interest in hybrid and electric vehicles, the battery, being one of the critical components, is receiving a lot of attention from designers and researchers. Two battery-modeling approaches, though seemingly different, share the same mathematical challenge of robust non-linear curve-fitting. The two methods are battery equivalent circuit model and battery system level thermal modeling using the linear time-invariant (LTI) method. Both modeling approaches involve curve-fitting testing data or data from advanced models to identify four parameters in a circuit model consisting of two pairs of RC elements. Such curve-fitting is mathematically a non-linear least-squares (LS) problem. Standard methods like the Levenberg-Marquardt (LM) method can be used for non-linear curve-fitting, but the LM method is known to be sensitive to initial conditions.

To meet the ever increasing requirements in the areas of performance, fuel economy and emission, more and more subsystems and control functions are being added to modern engines. This leads to a quick increase in the number of control parameters and consequently dramatic time and cost increase for engine calibration. To deal with this problem, the automotive industry has turned to model-based calibration for a solution. Model-based calibration is a method that uses modern Design of Experiments (DoE), statistical modeling and optimization techniques to efficiently produce high quality calibrations for engines. There are two major enablers for carrying out this method - fully automated engine control and measurement system, and advanced mathematical tools for DoE, modeling and optimization.

Good battery modeling is critical for energy management of electric vehicles and hybrid electric vehicles. Because of its simplicity and satisfactory performance, equivalent circuit models are widely used in this area. A frequently adopted equivalent circuit model is one that consists of an open-circuit voltage and a resistor in series with two sets of parallel resistor-capacitor combinations. This model performs well in describing battery transient behavior due to the dynamics of such physical phenomena as mass transport effects and double layer effects. Generic methods for obtaining the parameters of this model involve analyzing the battery voltage behavior under step changes of load current. The fact that the model has two time constants places a challenge on parameter identification.

Engine Electronic Throttle Control (ETC) systems are gaining success in high volume applications. This system helps to improve overall engine and vehicle performance, as well as facilitate the function integration of related control features. The requirement for an ETC system is that it fulfills the commanded throttle plate opening as quickly and accurately as possible. Because of nonlinearity of the electronic throttle system, gain-scheduled control is often used. A method to automatically tune the control for each operating region is needed. In this paper the engine electronic throttle is considered as having dominant linear dynamics for each operating region. A Two-Degree-of-Freedom (2-DOF) PID controller and a method of using Model Reference Adaptive Control (MRAC) algorithm to automatically tune the PID control gains are designed.

To meet the ever increasing requirements for engines and vehicles in the areas of performance, fuel economy, emission, and meanwhile reduce product development time, Hardware-in-the-loop (HIL) simulation is increasingly used in automotive control system development. Engine-in-the-loop (EIL) vehicle simulation, which is a specific form of HIL simulation, is an approach in which a physical engine (together with its control unit) is coupled to virtual vehicle and driver models through a high power, low inertia engine dynamometer in the engine test cell environment. EIL can be used to perform powertrain control development, as well as engine and vehicle performance evaluation. Because of its advantages in repeatability and flexibility etc., especially for transient operating mode study, EIL has become a powerful tool and will be more widely used in the near future. Design and implementation of an EIL vehicle simulation system is described.

The Electronic Throttle Control (ETC) system is more and more used and increasingly becoming a standard part of the engine. It controls the amount of air intake into the cylinders by precisely positioning the throttle plate at the desired opening. An ETC system provides the possibility of improving the overall engine and vehicle performance because with such a mechanism, the engine controller can decide and set the throttle position not only based on driver intention, but also taking into consideration the specific engine operation mode information, such as safety factors, emission constraints, etc. After the throttle position target is determined, the requirement for the ETC system is that the throttle plate should achieve the commanded position as accurately and as quickly as possible. In many cases the controller is designed by first establishing a model of the electronic throttle system using experimental identification.

To fulfill ever increasingly stringent emission regulations, a great many studies on engine control and catalytic converter performance have been made. Topics of great interest in this area, to name a few, include: the relationship between catalyst light-off time and air-fuel (A/F) ratio; the relationship between forced A/F ratio modulation and catalyst efficiency; the effects of phase-shifted A/F ratio modulation between banks of a dual bank engine, or among cylinders of a single manifold engine on catalyst efficiency; and methods of modeling and measuring the oxygen storage capacity of a catalytic converter by rich-lean transition, A/F ratio sweeping, or other on-line estimation methods. To undertake this type of research, an engine control system with necessary functions, especially with very flexible A/F ratio control capabilities, is needed.

To meet the ever increasing requirements for engines and vehicles in the areas of performance, fuel economy and emission, and reduce product development time, we see the need for an integrated development environment which combines engine rapid control prototyping (RCP) capability with real-time vehicle simulation capability using an engine dynamometer in the test cell. Design and implementation of such a system with the ADX universal high-speed system controllers are described. An application example of simulating an FTP-75 cycle in the test cell while the engine is under ADX control is presented. This system moves a lot of work from the whole vehicle environment to the engine test cell environment, and is a powerful tool for quick development and testing of control algorithms as well as calibration.