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This paper presents an energy-optimal deceleration planning system (EDPS) to maximize regenerative energy for electrified vehicles on deceleration events perceived by map and navigation information, machine vision and connected communication. The optimization range for EDPS is restricted within an upcoming deceleration event rather than the entire routes while in real time considering preceding vehicles. A practical force balance relationship based on an electrified powertrain is explicitly utilized for building a cost function of the associated optimal control problem. The optimal inputs are parameterized on each computation node from a set of available deceleration profiles resulting from a deceleration time model which are configured by real-world test drivings.

Eco-Approach and Departure (EAD) has been considered as a promising eco-driving strategy for vehicles traveling in an urban environment, where information such as signal phase and timing (SPaT) and geometric intersection description is well utilized to guide vehicles passing through intersections in the most energy-efficient manner. Previous studies formulated the optimal trajectory planning problem as finding the shortest path on a graphical model. While this method is effective in terms of energy saving, its computation efficiency can be further enhanced by adopting machine learning techniques. In this paper, we propose an innovative deep learning-based queue-aware eco-approach and departure (DLQ-EAD) system for a plug-in hybrid electric bus (PHEB), which is able to provide an online optimal trajectory for the vehicle considering both the downstream traffic condition (i.e. traffic lights, queues) and the vehicle powertrain efficiency.

Optimizing/maximizing regen braking in a hybrid electric vehicle (HEV) is one of the key features for increasing fuel economy. However, it is known [1] that maximizing regen braking by braking the rear axle on a low friction surface results in compromising vehicle stability even in a vehicle which is equipped with an ESP (Enhanced Stability Program). In this paper, we develop a strategy to maximize regen braking without compromising vehicle stability. A yaw rate stability control system is designed for a hybrid electric vehicle with electric rear axle drive (ERAD) and a “hang on” center coupling device which can couple the front and rear axles for AWD capabilities. Nonlinear models of the ERAD drivetrain and vehicle are presented using bond graphs while a high fidelity model of the center coupling device is used for simulation.

Test and verification procedures are a vital aspect of the development process for embedded control systems in the automotive domain. Formal requirements can be used in automated procedures to check whether simulation or experimental results adhere to design specifications and even to perform automatic test and formal verification of design models; however, developing formal requirements typically requires significant investment of time and effort for control software designers. We propose Signal Template Library (ST-Lib), a uniform modeling language to encapsulate a number of useful signal patterns in a formal requirement language with the goal of facilitating requirement formulation for automotive control applications. ST-Lib consists of basic modules known as signal templates. Informally, these specify a characteristic signal shape and provide numerical parameters to tune the shape.

Combatting the modification of automotive control systems is a current and future challenge for OEMs and suppliers. ‘Chip-tuning’ is a manifestation of manipulation of a vehicle's original setup and calibration. With the increase in automotive functions implemented in software and corresponding business models, chip tuning will become a major concern. Recognizing and reporting of tuned control units in a vehicle is required for technical as well as legal reasons. This work approaches the problem by capturing the behavior of relevant control units within a machine learning system called a recognition module. The recognition module continuously monitors vehicle's sensor data. It comprises a set of classifiers that have been trained on the intended behavior of a control unit before the vehicle is delivered. When the vehicle is on the road, the recognition module uses the classifier together with current data to ascertain that the behavior of the vehicle is as intended.

Steady-state, transient and dithering characteristics of emission conversion efficiencies of three-way catalysts on natural gas IC engine were investigated experimentally on a single-cylinder CFR engine test bench. Steady-state runs were conducted as references for specific engine emission levels and corresponding catalyst capacities. The steady-state data showed that conversion of HC will be the major problem since conversion of HC was effective only for a very narrow range of exhaust mixture. Unsteady exploration runs with both lean-to-rich and rich-to-lean transitions were conducted. These results were interpreted with a time scale analysis, according to which a qualitative oxygen storage model was proposed featuring the difference between oxygen absorption and desorption rates on the palladium catalysts.

Engine manufacturers have explored many routes to reducing the emissions of harmful pollutants and conserving energy resources, including development of after treatment systems to reduce the concentration of pollutants in the engine exhaust, using alternative fuels, and using alternative fuels with after treatment systems. Liquefied petroleum gas (LPG) is one alternative fuel in use and this paper will discuss emission measurements for several LPG vehicles. Regulated emissions were measured for five school buses, one box truck, and two small buses over a cold start Urban Dynamometer Driving Schedule (CS_UDDS), the Urban Dynamometer Driving Schedule (UDDS), and the Central Business District (CBD) cycle. In general, there were no significant differences in the gas phase emissions between the UDDS and the CBD test cycles. For the CS-UDDS cycle the total hydrocarbons and non-methane hydrocarbon emissions are higher than they are from the UDDS cycle.

The fact that, in our times, the execution of the exothermic process of combustion (‘heat release”) remains virtually uncontrolled is astonishing. Upon an attempt to rationalize this anomaly on historical grounds, technological means to rectify this astounding state of affairs are presented. They are based on the premise that, in the course of this process, the cylinder-piston enclosure is, in effect, a full-fledged chemical reactor. The salient feature of control is then active intervention into chemical reaction by turbulent jets. Principal elements of the control system are, as in any feedback mechanism, (1) sensors, (2) actuators and (3) a governor. The object of the first is to measure the profile of pressure - the useful output of the process. The second consists of a set of turbulent jet generators for injection of fuel and its mixing with air, as well as for ignition.

Quantifying Hybrid Electric Vehicle (HEV) emissions and fuel consumption is a difficult problem for a number of different reasons: 1) HEVs can be configured in significantly different ways (e.g., series or parallel); 2) the Auxiliary Power Unit (APU) can consist of a wide variety of engines, fuel types, and sizes; and 3) the APU can be operated very differently depending on the energy management system strategy and the type of driving that is performed (e.g., city vs. highway driving). With the future increase of HEV penetration in the vehicle fleet, there is an important need for government agencies and manufacturers to determine HEV emissions and fuel consumption. In this paper, several critical issues associated with HEV emissions and fuel consumption are identified and analyzed, using a sophisticated set of HEV and emission simulation modeling tools.

This paper is written to provide information on the fuel efficiency, emissions and energy cost of vehicles ranging from a pure electric (ZEV) to gasoline hybrid vehicles with electric range varying from 30 mi (50km) to 100 mi (160km). The Federal government s PNGV and CARB s ZEV have different goals, this paper explores some possibilities for hybrid-electric vehicle designs to meet both goals with existing technologies and batteries. The SAE/CARB testing procedures for determining energy and emission performance for EV and HEV and CARB s HEV ruling for ZEV credit are also critically evaluated. This paper intends to clarify some confusion over the comparison, discussion and design of electric- hybrid- and conventional- vehicles as well.

The concept of the paper stems from the premise that the process of “heat release” in engines involves in essence the evolution and deposition of exothermic energy generated by combustion-events that can be governed promptly by a feedback, adaptive micro-electronic control system. The key to its realization is the principle of DISC (Direct Injection Stratified Charge) engine, implemented by a multi-jet system. The background and the salient features of such a system, referred to as a CCE (Controlled Combustion Engine), have been described in a companion paper (SAE 951961). Presented here are fundamental aspects of the model of the exothermic process and the intrinsic properties of its control system.

Although various legislation and regulations have been adopted to promote the use of alternative-fuel vehicles for curbing urban air pollution problems, there is a lack of systematic comparisons of emission control cost-effectiveness among various alternative-fuel vehicle types. In this paper, life-cycle emission reductions and life-cycle costs were estimated for passenger cars fueled with methanol, ethanol, liquified petroleum gas, compressed natural gas, and electricity. Vehicle emission estimates included both exhaust and evaporative emissions for air pollutants of hydrocarbon, carbon monoxide. nitrogen oxides, and air-toxic pollutants of benzene, formaldehyde, 1,3-butadiene, and acetaldehyde. Vehicle life-cycle cost estimates accounted for vehicle purchase prices, vehicle life, fuel costs, and vehicle maintenance costs.

In practical applications, failures in the components of the control system can lead to improper, or even unstable, operation of the control loop. These failures can be associated with the process (abrupt change in the process dynamics), the measuring and manipulating devices (sensors, actuators) or the controller itself. It is therefore desired to design control system capable of handling such events in the sense that stability is guaranteed and performance degradation is minimized. The proposed formulation of the reliable performance problem involves the simultaneous minimization of the performance index for all considered failure scenarios. Employing the fractional representation theory, the reliable performance problem is formulated as a quadratically constrained control problem. The solution to this problem is discussed in this paper and an illustrative example is presented.