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This paper delves into the investigation of flatness-based active damping control for hybrid vehicle transmissions. The main objective is to improve the current in-production controller performances without the need for additional sensors or observers. The primary goals include improving torque setpoint tracking, enhancing robustness margins, and ensuring zero steady-state torque correction. The investigation proceeds in several steps: Initially, both the general differential flatness property and the identification of flat outputs in linear dynamical systems are revisited. Subsequently, the bond graph formalism is employed to deduce straightforwardly the dynamical equations of the system. Next, a new flat output of the vehicle transmission is identified and utilized to formulate the trajectory tracking controller to align with the required control objectives and to fulfill the system constraints.

Automotive Heating Ventilation and Air Conditioning (HVAC) system is essential in providing the thermal comfort to the cabin occupants. The HVAC noise which is typically not the main noise source in IC engine vehicles, is considered to be one of the dominant sources inside the electric vehicle cabin. As air is delivered through ducts and registers into the cabin, it will create an air-rush/broadband noise and in addition to that, any sharp edges or gaps in flow path can generate monotone/tonal noise. Noise emanating from the HVAC system can be reduced by optimizing the airflow path using virtual tools during the development stage. This paper mainly focuses on predicting the noise from the HVAC ducts and registers. In this study, noise simulations were carried-out with ducts and registers. A Finite Volume Method (FVM) based 3-dimensional (3D) Computational Fluid Dynamics (CFD) solver was used for flow as well as acoustic simulations.

Stringent requirements for high fuel economy and energy efficiency mandate using increasingly complex vehicle thermal systems in most types of electrified vehicles (xEVs). Enabling the maximum benefits of such complex thermal systems under the full envelope of their operating modes demands designing complex thermal control systems. This is becoming one of the most challenging problems for electrified vehicles. Typically, the thermal systems of such vehicles have several modes of operation, constituting nonlinear multiple-input/multiple-output (MIMO) dynamic systems that cannot be efficiently controlled using classical or rule based strategies. This paper covers the different steps towards the design of a model-based control (MBC) strategy that can improve the overall performance of xEV thermal control systems. To achieve the above objective, the latter MBC strategy is applied to control cooling of the cabin and high voltage battery.

The reduction of automotive emissions is instrumental in the fight against air pollution and its impact on global warming. This realization has empowered governments around the world to mandate lower levels of vehicle emissions requiring the Original Equipment Manufacturers (OEMs) to implement advanced aftertreatment technologies in their applications. Achieving emission levels as low as SULEV30 or SULEV20 would have been impossible only a couple of decades ago, however, these lower levels of emissions are now a possibility through advanced control strategies and aftertreatment systems. As a part of this mandate to lower emissions, OEMs are also continuously monitoring the health and performance of their aftertreatment and control components. The implementation of On Board Diagnostics (OBD) ensures that control systems are functioning robustly and the emission levels are achieved and maintained to high mileages for the life of the vehicle.

Mixture formation and combustion dynamics are the primary contributors to the performance and emission characteristics of direct-injected spark ignition (SI) engines. This requires assessing the benefits and tradeoffs of the design and control factors that influence mixing and the subsequent combustion event. In this study, Taguchi's L18 orthogonal array design of experiment (DoE) methodology has been applied to assess contributions and tradeoffs of varied compression ratio, piston bowl design, intake port tumble design, injector spray pattern, injection timing, injection pressure, exhaust gas recirculation (EGR) rate, and intake valve closing timing in a single-cylinder boosted gasoline direct injection (GDI) SI engine. This multiparameter study has been carried out across three speed-load conditions representative of typical automotive application operating ranges.

Vehicle multi-zone automatic Heating, Venting and Air Conditioning (HVAC) is the advanced form of the traditional air conditioning. The advantage of multi-zone automatic HVAC is that it allows the passengers of a vehicle to set a desired temperature for their own zone within the vehicle compartment. This desired temperature is then maintained by the HVAC system, which determines how best to control the available environment data to provide optimal comfort for the passengers. To achieve overall thermal comfort of the occupants in a vehicle, multi-zone HVAC takes things a step further by adding heated steering wheel and heated/vented seats to the overall HVAC control strategy. The heating and cooling of the occupants by this integrated system is performed by complex control algorithms in form of embedded software programs and Private LIN network. This paper describes the approach and tools used to develop, simulate and validate the multi-zone integrated climate control system.

In the NVH domain, the cooling module is an important subsystem in ground vehicles. Recently, with the development of small high output turbocharged internal combustion (IC) engines, cooling module noise and vibration has become more challenging. Furthermore, with plug-in hybrid electric vehicle (PHEV), in some cases the cooling fan could be operational while the IC engine is not running. This poses a significant challenge for cabin noise enhancement. Small turbocharged IC engines typically require higher cooling capacity resulting in larger fan size designs with higher speed. Accurate prediction of the unbalance loads generated by cooling fan and loads transferred to the body are critical for the Noise Vibration and Harshness (NVH) performance of the vehicle. If the NVH risk of cooling module operation is not well quantified and addressed early in the program, attempts to find solutions in post launch stage could be very expensive and not as effective.

There are many noise sources from the vehicle fuel system to generate noise inside a vehicle. Among them, the pressure pulsation due to the rapid opening and closing of gasoline engine injectors can cause undesirable fuel pulse noise. As the pressure pulsation propagates in the fuel supply line toward to rear end of the vehicle, the pressure energy is transferred from fuel lines to the vehicle underbody through clips and into the passenger compartment. It is crucial to attenuate the pressure pulsation inside the fuel line to reduce the fuel pulse noise. In this paper, a case study on developing an effective countermeasure to reduce the objectionable fuel pulse noise of a V8 gasoline injection system at engine idle condition is presented. First, the interior noise of a prototype vehicle was tested and the objectionable fuel pulse noise is exhibited. The problem frequency ranges of the pulse noise were identified.

This paper describes a reliable CAE methodology to model the linear vibratory behavior of windshields. The windshield is an important component in vehicle NVH performance. It plays an integral role in interior cabin noise. The windshield acts as a large panel typically oriented near vertical at the front of vehicle’s acoustic cavity, hence modeling it accurately is essential to have a reliable prediction of cabin interior noise. The challenge to model the windshield accurately rises from the structural composition of different types of windshields. For automotive applications, windshields come in several structural compositions today. In this paper, we will discuss two types of windshield glass used primarily by automotive manufacturers. First type is the typical laminated glass with polyvinyl butyral (PVB) layer and second type is the acoustic glass with PVB and vinyl layers. Acoustic glass improves acoustic characteristics of the glass in a frequency range of ~ 1200 Hz to ~4000 Hz.

Nowadays development of automotive HVAC is a challenging task wherein thermal comfort and safety are very critical factors to be met. HVAC system is responsible for the demisting and defrosting of the vehicle’s windshield and for creating/maintaining a pleasing environment inside the cabin by controlling airflow, velocity, temperature and purity of air. Fog or ice which forms on the windshield is the main reason for invisibility and leads to major safety issues to the customers while driving. It has been shown that proper clear visibility for the windshield could be obtained with a better flow pattern and uniform flow distribution in the defrost mode of the HVAC system and defrost duct. Defroster performance has received significant attention from OEMs to meet the specific global performance standards of FMVSS103 and SAE J902. Therefore, defroster performance is seriously taken into consideration during the design of HVAC system and defroster duct.

Within a hybrid electric vehicle, given a power request initiated by pedal actuation, a portion of overall power may be generated by fuel within an internal combustion engine, and a portion of power may be taken from or stored within a battery via an e-machine. Generally speaking, power taken from a vehicle battery must eventually be recharged at a later time. Recharge energy typically comes ultimately from engine generated power (and hence from fuel), or from recovered braking energy. A hybrid electric vehicle control system attempts to identify when to use each type of power, i.e., battery or engine power, in order to minimize overall fuel consumption. In order to most efficiently utilize battery and fuel generated power, many HEV control strategies utilize a concept wherein battery power is converted to a scaled fueling rate.

Acoustic comfort of automotive cabins has progressively become one of the key attributes of passenger comfort within vehicle design. Wind noise and the heating, ventilation, and air conditioning (HVAC) system noise are two of the key contributors to noise levels heard inside the car. The increasing prevalence of hybrid technologies and electrification has an associated reduction in powertrain noise levels. As such, the industry has seen an increasing focus on understanding and minimizing HVAC noise, as it is a main source of noise in the cabin particularly when the vehicle is stationary. The complex turbulent flow path through the ducts, combined with acoustic resonances can potentially lead to significant noise generation, both broadband and tonal.

Battery state-of-charge (SOC) is critical information for the vehicle energy management system and must be accurately estimated to ensure reliable and affordable electrified vehicles (xEV). However, due to the nonlinear temperature, health, and SOC dependent behaviour of Li-ion batteries, SOC estimation is still a significant automotive engineering challenge. Traditional approaches to this problem, such as electrochemical models, usually require precise parameters and knowledge from the battery composition as well as its physical response. In contrast, neural networks are a data-driven approach that requires minimal knowledge of the battery or its nonlinear behaviour. The objective of this work is to present the design process of an SOC estimator using a deep feedforward neural network (FNN) approach. The method includes a description of data acquisition, data preparation, development of an FNN, FNN tuning, and robust validation of the FNN to sensor noise.

The idea of improved efficiency without compromising the “fun to drive” aspect has renewed the auto industry’s interest toward electrification and hybridization. Electric drives gain from having multiple gear ratios which can use advantageous operating set points thus increasing range. Furthermore, they benefit significantly from frequent decelerations and stopping as is experienced in city driving conditions. To recuperate as much energy as possible, deceleration is done at high torque. This presents an interesting but serious sound quality issue in the form of highly tonal whine harmonics of rapidly changing gears that do not track with vehicle speed thus being objectionable to the vehicle occupants. This paper presents an NVH target setting process for a hybrid electric transmission being integrated into two existing vehicles, one belonging to the premium segment and another aimed at enthusiasts with off-road applications.

The application of Computational Fluid Dynamics (CFD) for three-dimensional (3D) combustion analysis coupled with detailed chemistry in engine development is hindered by its expensive computational cost. Chemistry computation may occupy as much as 90% of the total computational cost. In the present paper, a new two-step iso-octane combustion model was developed for spark-ignited (SI) engine to maximize computational efficiency while maintaining acceptable accuracy. Starting from the model constants of an existing global combustion model, the new model was developed using an approach based on sensitivity analysis to approximate the results of a reference skeletal mechanism. The present model involves only five species and two reactions and utilizes only one uniform set of model constants. The validation of the new model was performed using shock tube and real SI engine cases.

Simplified load path models (SLMs) of the body in white (BIW) are an important tool in the body structure design process providing a highly flexible, idealized concept model to explore the design space through load path evaluation, material selection, and section optimization with rapid turnaround. In partnership with Altair Engineering, the C123 process was used to create and optimize SLMs for BIW models at FCA US LLC. These models help structures engineers to develop efficient load paths, sections, and joints for improved NVH as ultra-high-strength steels enable thinner gauges throughout the body structure. A few key differences in the SLM modeling method are contrasted to previous simplified BIW modeling methods. One such example is the parameterization of cross sections through response surface models rather than using contemporary finite element descriptions of arbitrary cross sections.

Due to stringent environmental requirements, the vehicle under-hood and underbody temperatures have been steadily increasing. The increased temperatures affect components life and therefore, more thermal protection measures may be necessary. In this paper, we present an algorithm for estimation of automotive component life due to thermal effects through the vehicle life. Traditional approaches consider only the maximum temperature that a component will experience during severe driving maneuvers. However, that approach does not consider the time duration or frequency of exposure to temperature. We have envisioned a more realistic and science based approach to estimate component life based on vehicle duty cycles, component temperature profile, frequency and characteristics of material thermal degradation. In the proposed algorithm, a transient thermal analysis model provides the exhaust gas and exhaust surface temperatures for all exhaust system segments, and for any driving scenario.

A vehicle driving down the road naturally pitches, rolls and heaves due to road inputs (for example, bumps, potholes, driving dynamics, etc.) and also due to the influence of aerodynamic forces. The vehicle attitude changes directly as a result of aerodynamic forces that can be seen during wind tunnel testing of production level vehicles, with some measurements possible in order to evaluate the aerodynamics effects. This naturally occurring phenomenon is not always represented in aerodynamics simulations, either for reduced scale models or computational fluid dynamics (CFD) simulations or even rigid body full scale testing. It can be shown through visual techniques how much deflection is typically occurring, including both vehicle attitude changes as well as vehicle body distortions. From the analysis, an adjustment to the CFD models can be made to compensate for the aerodynamics effects.

Engine air induction shell noise is a structure borne noise that radiates from the surface of the air induction system. The noise is driven by pulsating engine induction air and is perceived as annoying by vehicle passengers. The problem is aggravated by the vehicle design demands for low weight components packaged in an increasingly tight under hood environment. Shell noise problems are often not discovered until production intent parts are available and tested on the vehicle. Part changes are often necessary which threatens program timing. Shell noise should be analyzed in the air induction system design phase and a good shell noise analytical process and targets must be defined. Several air induction clean side ducts are selected for this study. The ducts shell noise is assessed in terms of material strength and structural stiffness. A measurement process is developed to evaluate shell noise of the air induction components. Noise levels are measured inside of the clean side ducts.

This research proposes a control system for Spark Ignition (SI) engines with external Exhaust Gas Recirculation (EGR) based on model predictive control and a disturbance observer. The proposed Economic Nonlinear Model Predictive Controller (E-NMPC) tries to minimize fuel consumption for a number of engine cycles into the future given an Indicated Mean Effective Pressure (IMEP) tracking reference and abnormal combustion constraints like knock and combustion variability. A nonlinear optimization problem is formulated and solved in real time using Sequential Quadratic Programming (SQP) to obtain the desired control actuator set-points. An Extended Kalman Filter (EKF) based observer is applied to estimate engine states, combining both air path and cylinder dynamics. The EKF engine state(s) observer is augmented with disturbance estimation to account for modeling errors and/or sensor/actuator offset.