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Improving vehicle response through advanced knowledge of traffic behavior can lead to large improvements in energy consumption for the single isolated vehicle. This energy savings across multiple vehicles can even be larger if they travel together as a cohort in harmonization. Additionally, if the vehicles have enough information about their immediate path of travel, and other vehicles’ in that path (and their respective critical forward-looking information), they can safely drive close enough to each other to share aerodynamic load. These energy savings can be upwards of multiple percentage points, and are dependent on several criteria. This analysis looks at criteria that contributes to energy savings for a cohort of vehicles in synchronous motion, as well as describes a study that allows for better understanding of the potential benefits of different types of cohorted vehicles in different platoon arrangements.

Safety control and protection strategy of high-voltage system of electric vehicles include analysis of circuit condition before connection to high voltage terminal, transient current prevention for capacitive load, real-time monitoring and analysis of high-voltage system during operation, disconnecting strategy of high voltage terminals, vehicle dynamic safety and cooperative management of electrical systems, etc. Monitoring and analysis of some critical parameters of high voltage system such as insulation, electrical harness and connector condition are the basis and difficulties in high-voltage safety and protection. This paper presents several mathematical models of monitoring critical parameters, and experiments were also done to evaluate the model. Disadvantages of the commonly used calculation method are discussed. Single point insulation defect model is introduced and diagnosis method of multiple points defect is also discussed.

In land vehicles with high-power electrical loads, other than the low-voltage DC bus (14V, 28V, or 42V) for the low-power conventional loads, a high-voltage bus, e.g., 200V DC, is required for high-power loads such as hotel loads and electrically-assisted propulsion systems. In addition, some advanced electrical loads including luxury loads and AC power point require 120V, 60Hz AC voltage. These land vehicles include heavy duty, fire fighting, and military vehicles. There are two traditional approaches in obtaining a dual DC voltage bus system. The first one is to obtain the low-voltage DC from the alternator and boost it to the high-voltage DC. The second method is to obtain the high-voltage DC directly from the alternator and reduce it to the low-voltage. Both approaches require additional step-up or step-down power conversion stages, which inherently result in a reduced efficiency. In this paper, a new approach with a 28V/200V dual voltage alternator is considered.

Demands for higher fuel economy, performance, reliability, convenience, as well as reduced emissions push the automotive industry to seek electrification of ancillaries and engine augmentations. In cars of the future, throttle actuation, steering, anti-lock braking, rear-wheel steering, active suspension and ride-height adjustment, air-conditioning, and electrically heated catalyst will all benefit from the electrical power system. Therefore, a higher system voltage, such as the proposed 42V, is necessary to handle these new introduced loads. In this paper, an overview of the systems that will benefit from the 42V bus is presented. Effects of the new introduced electrical loads on the electrical power systems of conventional cars are described. Dynamic characteristics of each load for a typical drive cycle are defined. In addition, system level issues and vehicle performances such as fuel economy are addressed.

With the increase of hotel and ancillary loads and replacement of engine driven mechanical and hydraulic loads with electrical loads, automotive systems are becoming more electric. This is the concept of More Electric Cars (MEC) that necessitates a higher system voltage, such as the proposed 42V, for conventional cars. In this paper, the development of the 42V electric power system for vehicle applications is reviewed. The system architecture and motor drive problems associated with the 42V electric power system are analyzed. Solutions to these problems are also discussed.

This paper presents that low-voltage (42V) current intensive Switched Reluctance Machine (SRM) based traction systems are feasible for lightly hybridized vehicles. Power electronic drive as well as electric machine issues are comprehensively addressed. Five different SRM drivers for low-voltage and high-voltage machines are studied. Suitability of the proposed low-voltage, high-current drives is elaborated. Furthermore, four machines with the rating of 7.5 kW are designed and simulated. These traction machines have 6/4 and 8/6 SRM configurations with the operating voltage of 42V and 300V. Higher torque density is the main advantage of the low-voltage machines compared to the high-voltage machines. In addition, 6/4 SRMs have better performance.

The traditional method of dynamic characterization of elastomers used in industry has largely been based on sinusoidal input excitation. Discrete frequency sine wave signals at specified amplitudes are used to excite the elastomer in a step-sine sweep fashion. This paper will examine new methods of characterization using various broadband input excitations. These different inputs include continuous sine sweep (chirp), shaped random, and acquired road profile data. Use of these broadband data types is expected to provide a more accurate representation of conditions seen in the field, while helping to eliminate much of the interpolation that is inherent with the classic discrete step-sine technique. Results of the various input types are compared in this paper with those found using the classic discrete step-sine input.

A high voltage battery is an essential part of hybrid electric vehicles (HEVs). It is imperative to precisely estimate the state of charge (SOC) and state of health (SOH) of battery in real time to maintain reliable vehicle operating conditions. This paper presents a method of estimating SOC and SOH through the incorporation of current integration, voltage translation, and Ah-throughput. SOC estimation utilizing current integration is inadequate due to the accumulation of errors over the period of usage. Thus voltage translation of SOC is applied to rectify current integration method which improves the accuracy of estimation. Voltage translation data is obtained by subjecting the battery to hybrid pulse power characterization (HPPC) test. The Battery State of Health was determined by semi-empirical model combined with accumulated Ah-throughput method. Battery state of charge was employed as an input to estimate damages accumulated to battery aging through a real-time model.

Connected vehicles have the potential to transform the way we commute and travel in a multitude of ways. Vehicles will cooperate and coordinate with each other to solve problems appropriate for the environment in which they are operating. In this paper, we focus on the development of test equipment that includes the infrastructure and vehicles to measure and record all of the information necessary to quantify the performance of cooperative driving algorithms in realistic scenarios. The system allows tests to include real vehicles on the track and virtual vehicles in a digital twin. Real and virtual vehicles interact through the road-side units and test facility network, allowing each test vehicle to receive messages from virtual vehicles as well as the infrastructure. Messages transmitted from the test vehicles are received in the digital twin, allowing the real vehicle to interact with virtual vehicles.

A more accurate combustion model, based on Fluent simulations including the effect of flame stretching and extinction, has been added to cycle and road simulations of an Adaptive Cycle Engine (ACE), where compressions and expansions do not follow a predefined sequence. Also, engine speed data from the Argonne Downloadable Dynamometer Database is used in the road simulations in lieu of the original constant-speed model. Results show a drop in predicted steady-state brake efficiency and bmep around 15% relative to the model using a standard Wiebe function for heat release rate. Performance on road cycles is not greatly affected by the delayed combustion since the relationship between expansion mass and work is largely unchanged. Even with the refined model, future ACE-equipped vehicles are expected to be competitive with electric powertrains in pre-tax cost and overall emissions.

Predictive Signal Phase and Timing (SPAT) message set is one fundamental building block for vehicle-to-infrastructure (V2I) applications such as Eco-Approach and Departure (EAD) at traffic signal controlled urban intersections. Among the two complementary communication methods namely short-range sidelink (PC5) and long-range cellular radio link (Uu), this paper documents the work with long-range link: the complete data chain includes connecting to the traffic signals via existing backhaul communication network, collecting the raw signal phase state data, predicting the signal state changes and delivering the SPAT data via a geofenced service to requests over HTTP protocols. An Application Programming Interface (API) library is developed to support various cellular data transmission reduction and latency improvement techniques.

Large channel count data acquisition systems have seen increasing use in the acquisition and analysis of rotating machinery, these systems have the ability to generate very large amounts of data for analysis. The most common operating measurement made on powertrains or automobiles on the road or on dynamometers has become the order track measurement. Order tracking analysis can generate a very large amount of information that must be analyzed, both due to the number of channels and orders tracked. Analysis methods to efficiently analyze large numbers of Frequency Response Function (FRF) measurements have been developed and used over the last 20 years in many troubleshooting applications. This paper develops applications for several FRF based analysis methods as applied for efficient analysis of large amounts of order track data.

This paper presents a methodology to optimize the blending of charge-depleting (CD) and charge-sustaining (CS) modes in a multi-mode plug-in hybrid electric vehicle (PHEV) that reduces overall energy consumption when the selected route cannot be completely driven in all-electric mode. The PHEV used in this investigation is the second-generation Chevrolet Volt and as many as four instrumented vehicles were utilized simultaneously on road to acquire validation data. The optimization method used is dynamic programming (DP) paired with a reduced-order powertrain model to enable onboard embedded controller compatibility and computational efficiency in optimally blending CD, CS modes over the entire drive route.

This research investigates the energy savings achieved through eco-driving controls in connected and automated vehicles (CAVs), with a specific focus on the influence of powertrain characteristics. Eco-driving strategies have emerged as a promising approach to enhance efficiency and reduce environmental impact in CAVs. However, uncertainty remains about how the optimal strategy developed for a specific CAV applies to CAVs with different powertrain technologies, particularly concerning energy aspects. To address this gap, on-track demonstrations were conducted using a Chrysler Pacifica CAV equipped with an internal combustion engine (ICE), advanced sensors, and vehicle-to-infrastructure (V2I) communication systems, compared with another CAV, a previously studied Chevrolet Bolt electric vehicle (EV) equipped with an electric motor and battery.