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Progress in Automotive Transmission Technology

Progress in Automotive Transmission Technology

Much progress has been made in the development of automotive transmissions over the past 20 years, e.g., an increased speed number, expanded ratio spread and improved efficiency and shift quality. Automotive transmissions are moving toward electrification in response to stringent legislation on emissions and the pressing demand for better fuel economy. 

This paper reviews progress in automotive transmission technology. Assisted by computer-aided programs, new transmission schemes are constantly being developed. We therefore first introduce the synthesis of the transmission scheme and parameter optimization. 

We then discuss the progress in the transmission technology of a conventional internal combustion engine vehicle in terms of new layouts; improved efficiency; noise, vibration and harshness technology; and the shifting strategy and control technology. 

As the major development trend, transmission electrification is subsequently discussed; this discussion includes the configuration design, energy management strategy, hybrid mode shifting control, single-speed and multi-speed electric vehicle transmission and distributed electric drive. 

Finally, a summary and outlook are presented for conventional automotive transmissions, hybrid transmissions and electric vehicle transmissions. 

With pressing demands to reduce emissions and improve fuel economy, automotive transmissions have evolved over the past 20 years while rapidly progressing toward electrification. 

Conventional automotive transmissions for the internal combustion engine (ICE) are generally classified into manual transmission (MT), automated manual transmission (AMT), automatic transmission (AT), dual-clutch transmission (DCT) and continuously variable transmission (CVT). 

This review focuses on the progress of AT, DCT and CVT because they largely account for the development of transmission technology in the past 20 years and have gradually replaced MT and AMT in passenger cars. 

Automotive transmissions are undergoing electrification to meet stringent legislations pushing for CO2 reduction. 

As electromechanical coupling systems, transmissions in hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs) are important in terms of achieving different driving modes, such as series, parallel and power-split modes. 

With the integration of the electric motor (EM) into conventional ATs, DCTs and CVTs are examples of transmission electrification and are normally realized by adding a hybrid module or replacing the launching element with a hybrid module.

Such add-on solutions have excellent inheritance because most parts can be shared between conventional transmissions and hybrid transmissions, which facilitates modular design and manufacture. 

In contrast to add-on solutions, dedicated hybrid transmissions (DHTs) are completely newly developed for HEVs and PHEVs. The complexity of a mechanical system is generally lower than that of conventional multispeed transmissions. 

As for electric vehicles (EVs), single-speed gearboxes are most commonly used today. It is not necessary for an EV to have a complex multi-speed transmission owing to the torque and efficiency characteristics of the EM. 

However, a two- or three-speed transmission can benefit the miniaturization of the EM in terms of reducing the EM peak torque. Furthermore, energy consumption can be reduced by optimizing the operating points of the EM through gear shifting. 

Many companies have therefore developed twoor three-speed transmissions for EVs. To improve the efficiency and reduce weight, EV transmission tends to be fully integrated with the EM and power electronics. 

The distributed electric drive is one direction of the research and development (R&D) of EVs, and it has attracted much attention because of its simple vehicle architecture and high drive efficiency. Some in-wheel motors are close to industrialization.

Along with the development of HEVs, PHEVs and EVs, automotive transmission technology is currently in a transition phase moving toward electrification. It is thus necessary to review and provide an outlook for the development of automotive transmission. 

The remainder of the paper is organized as follows. Section 2 introduces the synthesis of a transmission scheme and parameter optimization. Section 3 discusses the progress in the transmission technology of a conventional ICE vehicle. Section 4 presents the state of the art of electrified transmission technology for HEVs, PHEVs and EVs. 

1. Synthesis of a Transmission Scheme and Parameter Optimization

Regarding the development of automotive transmissions, the first step is to find a competitive transmission scheme with high power density, high efficiency and low R&D costs. This section introduces the theory and methodology of the synthesis of the transmission scheme. The parameter optimization of transmission schemes is also reviewed in this section. 

a. Synthesis of the Transmission Scheme 

An AT is a system having multiple degrees of freedom (DOFs) mechanically connected by several planetary gear sets (PGSs), parallel-axis gear pairs (PGPs) and shifting elements (SEs). It achieves different gear ratios by engaging different SEs to reduce the number of DOFs of the system. 

Depending on the numbers of PGSs, SEs and DOFs, the maximum number N of candidate transmission schemes can be calculated as where L, n and p are, respectively, the numbers of SEs, DOFs and PGSs. 

Taking the synthesis problem of a transmission scheme with three PGSs, three SEs and four DOFs as an example, the total number of candidate transmission schemes is about 1.9 billion, among which it is difficult to find the best. Several synthesis methods have been proposed in the literature to solve this complex problem.

b. Parameter Optimization

The performance of a transmission scheme in terms of, for example, the gear ratios, mechanical efficiency and structural compactness will depend on design parameters. It is therefore essential to find the optimal parameters with which to design a transmission scheme with good performance. 

However, this is difficult because there are a great many parameters and many optimization goals. Most work nowadays focuses on the parametric optimization of the stationary ratios of PGSs. Ideal transmission ratios for all gears are usually given in advance by experienced engineers as the initial optimization target. 

The transmission ratio of each gear is determined by the stationary ratios of PGSs. Some numerical algorithms, such as dynamic programming, ant colony, particle swarm and genetic algorithms, have been shown to be effective for solving such problems.

There remain strict requirements in addition to the transmission ratios in the parametric design of a transmission scheme. However, the computational effort increases dramatically once these are taken into account. 

For conventional ATs, how to build a parametric optimization model considering as many factors as possible will be another ongoing research hotspot. 

Chen proposed an improved minimum and maximum principle to optimize the detailed gear parameters (including the gear modulus, gear teeth number and gear width) of a two-speed transmission scheme and built an optimization model for the optimal dynamic and economic performance. 

For DHTs in HEVs and PHEVs, the main focus is energy management and mode shifting control. However, the coordination of multiple power sources is also an important factor, and few published works have focused on structural parametric optimization design.

2. Progress in the Transmission Technology of a Conventional ICE Vehicle 

This section gives a general review of the latest developments of conventional automotive transmission for the ICE. The transmission layout synthesis, efficiency improvement, noise, vibration and harshness (NVH) technology, shifting strategy and control technology are discussed separately.

a. Transmission Layout Synthesis 

Novel AT and DCT schemes have continuously emerged in recent years with an increasing number of speeds. A growing number of automakers are introducing these novel multi-speed transmissions to their vehicles, as a part of a continuing effort to improve the drivability and fuel economy of their vehicles. 

On the one hand, the highest gear ratio has been decreased to improve fuel economy when a vehicle is cruising. On the other hand, the lowest gear ratio has been increased to improve drivability when a vehicle is launching or creeping. 

The increasing speed number allows for smaller gear steps that provide comfort and smooth shifts. CVT schemes have not changed greatly. The main type is still the chain or belt drive. Jatco integrated an auxiliary gearbox with one Ravigneaux gear set (RGS) and three SEs to achieve a wider ratio spread. Other CVT concepts, such as the toroidal variator, are still far from industrialization.

b. Efficiency Improvement

Transmissions have tended to have more speeds in recent years because of legislative pressure relating to CO2 reductions and fuel economy. However, driving simulations indicate that increasing the speed number beyond 10 will not improve the fuel economy appreciably. 

Different optimization approaches have therefore been investigated for mechanical and hydraulic systems to improve transmission efficiency.

c. NVH Technology 

The noise and vibration arising from automotive transmission are transmitted to passengers through airborne and structureborne paths and lead to discomfort. Hence, the NVH problem in automotive transmission affects the vehicle driving comfort. 

Whining, rattling, clunking, shifting and bearing noises are the five main types of noise in automotive transmission. The whining noise is related to two main excitations of loaded gear pairs: transmission error and time-varying mesh stiffness. 

The transmission error is defined as the deviation of the actual meshing position from the theoretical position, which is strongly affected by gear manufacturing errors, assembly errors and tooth deformations. 

The timevarying mesh stiffness arises from the varying number of engaging teeth. The rattling noise is induced by the backlash of loose parts, such as the forward and backward vibrations of unloaded gear pairs and synchronizers. 

This type of noise can be typically found in DCTs because of the coupling of PGPs and synchronizers, especially at idling and low speeds. The clunking noise arises at the moment that the flanks of active components knock against each other. 

A shifting noise occurs when the synchronizer or clutch is not functioning correctly. This type of noise depends on tooth errors and the shift strategy and is an important factor in evaluating the NVH quality of automotive transmission. 

Bearing noise is always masked by other types of noise unless damage occurs, and it increases in magnitude rapidly as the level of damage increases. Damage can therefore be diagnosed according to noise characteristics in early stages. 

The noise in automotive transmissions is transmitted to passengers as airborne noise and structure-borne noise, as shown in Fig. 12. The airborne noise is directly transmitted to passengers from the excitation source or radiated through the gearbox. 

The structure-borne noise is generated by an excitation source and transmitted to passengers through the shafts, bearings, mountings and car body. Active and passive measures are often adopted to improve the NVH quality of automotive transmissions. 

Active measures are mainly concentrated on addressing noise sources. A high-contact ratio gear, helical gear, modified tooth profile and high-quality tooth surface can reduce the gear whining noise. 

Minimizing the backlash and the inertia of loose parts, optimizing the synchronizer design and reducing torsional vibration from the ICE can help reduce the rattling noise. 

Furthermore, a torsional damper, dual mass flywheel or pendulum absorber is often placed between the engine and transmission to reduce vibration and fluctuation from the ICE and thus effectively suppress the rattling noise and vibration of the gearbox. 

Passive measures relate to transmission routes of structure-borne noise from the noise source to the car body. 

Examples of passive measures include increasing the stiffness of gear bodies, shafts, bearings and housings and separating the natural frequencies of these components and tuning the transmission mounting. 

d. Shifting Strategy and Control Technology 

The biggest complaint of customers relating to ATs and DCTs relates to the shift quality. The control of the shifting process is therefore important. Transmission manufacturers improve shift quality through both hardware and software development. 

In terms of hardware development, a directly operating solenoid valve is used in novel ATs and DCTs to improve the control accuracy. 

A torque converter with a flat and smalldiameter torus and a clutch hub with high-strength aluminum are applied in the Aisin 10-speed longitudinal AT, which reduces rotational inertia to realize a short shifting time. 

The piston chamber volume of each SE is also reduced to prevent a long shift response due to piston or cylinder movement in clutch engagement. In terms of software development, numerous studies have investigated shifting strategies and control technologies. 

The shifts in ATs and DCTs are clutch-to-clutch shifts without power interruption. During torque transference from the off-going clutch to the on-coming clutch and speed synchronization from the current gear to the target gear, drivers expect a fast and smooth transition without drivetrain jerking, resulting in a demand for a high-quality shift. 

The two primary challenges for wet-clutch control are (i) the intrinsically complex and nonlinear behavior and (ii) the diversification of the dynamics over time due to changes in load, oil temperature and wear. 

Studies have focused on developing dynamic models of automotive transmissions in the shifting process. Relevant studies have also concentrated on different control approaches using a learning algorithm in the clutch control system. 

For instance, the two-level nonlinear model predictive controller (NMPC) and iterative learning controller (ILC) for wet-clutch control have been compared. 

Meanwhile, the potential of several model-based (i.e., NMPC, ILC and iterative optimization) and model-free (i.e., genetic-based machine learning and reinforcement learning) learning strategies have been analyzed for the control of wet clutches. 

There are generally three phases in clutch-to-clutch shifts: the fill phase, torque phase and inertia phase. The clutch fill control is affected by many factors, such as characteristics of the clutch actuation system, oil temperature and engine speed. 

Inaccurate clutch fill control can result in either an under-fill or an over-fill. It is necessary to implement methodologies in clutch fill control. Clutch fill control was improved to some extent using a new customized numerical dynamic programming method with pressure sensors. 

An adaptive sliding mode observer has been implemented to improve the online estimation of the turbine torque and hence improve the accuracy of the clutch pressure estimation in the fill phase. 

In terms of control strategies for the torque phase, models and algorithms have been proposed according to the dynamic characteristics of the clutch-to-clutch shift. 

Control strategies for upshifts and downshifts have been proposed, and a clutch torque controller has been designed for the torque phase on the basis of the proportional-integral-derivative (PID) control algorithm. 

A simple and robust controller design, which is based on the actuator dynamics and the clutch slip dynamics and has consistent performance under different initial conditions, has been presented. 

In terms of control strategies for the inertia phase, a combination of sliding mode control and adaptive feedback linearization has been used to achieve the desired reference tracking for the slip of the on-coming clutch. 

A modelbased nonlinear gearshift controller was designed employing the back-stepping method to improve the shift quality of vehicles with DCT during the inertia phase. 

A new nonlinear control method, especially applied in the inertia phase, was developed to deal directly with model parameter variation. It can be designed using a method involving three steps: steady-state control, reference dynamics feedforward control and PID feedback control. 

The coordinated control of the engine and transmission has greatly improved the shift quality and clutch durability. This method is widely applied for the inertia phase of clutch-to-clutch shifts. 

To compensate for the effects of build-to-build and lifecycle variations on shift quality, it is necessary to use adaptive control methods in shift control strategies. 

An adaptive system not only continuously monitors its own performance in relation to a given optimal condition but also modifies its own control parameters in a closed loop so as to approach the optimized performance. 

It has been experimentally demonstrated that clutch adaptive control strategies for the dry DCT not only reduce the level of jerk and frictional energy loss but also satisfy different starting intentions of the driver. 

Kim proposed an advanced shift controller that supervises the shift transients with adaptive compensation. The control input is updated through a learning process to adjust subsequent shifts on the basis of the continuous monitoring of shift performance and environment variations. 

Shi proposed adaptive control strategies for the inertia phase and torque phase. Shift quality is evaluated by monitoring the speed deviation and time difference. Test results verify that the proposed control strategies improve the shift quality effectively. 

DCT sets a benchmark for the shift time, giving the driver a quick response to the acceleration requirement. Control strategies have been developed for CVTs and ATs to compete with DCTs in terms of a shorter shift time. 

Jatco used stepwise shift control to improve the acceleration feeling of CVT. BMW proposed control strategies for complex shift events to cover situations where the target gear is normally reached by passing through intermediate gear steps. 

Through simultaneous actuation of various SEs, two sequential shifts are executed continuously. The overall shift duration can thus be reduced to achieve a fast shift performance. Aisin announced that its 10-speed longitudinal AT has a faster shift than the benchmarked AT and DCT.

3, Electrified Transmission Technology for HEVs/PHEVs/EVs 

This section reviews the progress of automotive transmissions for HEVs/PHEVs/EVs. The configuration design, energy management strategy, hybrid mode shifting control, EV transmission and distributed-drive EV are discussed separately. 

a. Configuration Design 

HEVs and PHEVs generally have one ICE and one or two EMs. Although the battery capacity differs between HEVs and PHEVs, the structural requirements for the drive system are the same. As previously described, HEV and PHEV transmissions can be simply divided into two types, namely add-on transmissions and DHTs [118], as shown in Fig. 13. 

On the basis of conventional automotive transmissions, many manufacturers have developed a variety of hybrid configurations. ZF, Mercedes-Benz and Hyundai introduced P2 systems based on their own mature ATs. 

Jatco and Chery developed P2 systems based on CVTs. VW proposed a P2 hybrid system based on its own DCT. BYD also proposed a hybrid system based on DCT, but this is a P3 configuration. Unlike the add-on solution, the DHT breaks the structural constraints of conventional transmissions. 

As the earliest DHT, the Toyota Hybrid System (THS) provided the direction for subsequent development in configuration design. As technology advanced, Toyota introduced a fourthgeneration hybrid system, as shown in Fig. 14, and this system is now widely applied. 

GM proposed two hybrid systems, namely Voltec-I and Voltec-II. The secondgeneration system Voltec-II is shown in Fig. 14 and is used for the Volt, Malibu and Cadillac CT6. Compared with the THS, Voltec-II has more operating modes but more PGSs and SEs. 

Corun developed a hybrid system with multiple modes using an RGS and two SEs [122], as shown in Fig. 14. The above schemes are based on PGSs. In addition, companies such as Honda and SAIC have developed DHTs based on PGPs as shown in Fig. 14. 

b. Energy Management Strategy 

Energy management strategies for HEVs and PHEVs have been extensively discussed in the literature over the last decade. Figure 15 shows that energy management strategies can be generally classified into optimization-based control strategies and rule-based control strategies. 

Optimization-based control strategies use analytical or numerical optimization algorithms to minimize the cost function regarding fuel consumption, emissions or driving performance. 

Optimization-based control strategies can be divided into global optimization and real-time optimization. If the optimization relies on knowledge of past or future power demands over a fixed and known driving cycle, a global optimal solution can be found. 

Because global optimization cannot be implemented directly for real-time energy management, it is referred to as non-causal. However, global optimization is useful in providing a control benchmark for designing rules or comparing with other control strategies. 

The strategies categorized under global optimization include linear programming, stochastic programming, dynamic pro gramming, genetic algorithms, simulated annealing, game theory and optimal control theory. 

In contrast to global optimization, real-time optimization can be implemented online with an instantaneous cost function based on the system variable and measurement data. 

Real-time optimization consists of an equivalent fuel consumption minimization strategy, decoupling control, robust control, model predictive control and intelligent control. 

Rule-based control strategies determine the control action at each moment by predefining a set of rules, which are designed in accordance with heuristics, intuition, human expertise, and mathematical models and, usually, without a priori knowledge of driving information.

By means of simulation or calibration, the strategies are then precisely adjusted aiming at obtaining satisfactory fuel consumption results.

Although rule-based control strategies are generally unable to guarantee optimality, their main advantage lies in their simplicity and effectiveness, which makes them easy to implement on actual HEVs and PHEVs. 

Rule-based control strategies are subcategorized into deterministic rule-based control strategies and fuzzy-rule-based control strategies. In deterministic rule-based control strategies, rules are designed via pre-computed look-up tables with the aid of enginebrake-specific fuel consumption. 

Such strategies can be further classified into thermostat (on/off) control strategies, power follower strategies, modified power follower strategies and state machine-based strategies. 

A fuzzy-rule-based control strategy, the advantages of which are its robustness to measurement noise and component variability along with its adaptation, is an extension of the deterministic rule-based control strategy. It is suitable for multi-domain, nonlinear, time-varying systems, such as HEVs. 

Fuzzy-rule-based control strategies can be further categorized into conventional, adaptive and predictive strategies. 

Driving modes of HEVs and PHEVs depend on the transmission scheme. A mode shift map, which decides the timing and sequence of switching between modes, can be designed according to the abovementioned energy management strategies. 

Unlike HEVs, PHEVs can be charged using outlets of the power grid. Additionally, PHEVs have larger battery capacity and a more powerful motor, which indicates that they offer a longer driving distance and an improved driving ability in electric-only mode than HEVs. 

This has given a new dimension to the energy management strategies as PHEVs can operate in both charge depleting (CD) and charge sustaining (CS) modes. 

Correspondingly, the transmission structure is modified for PHEV application; for example, an OWC is added to the THS to enable the vehicle to be driven using two motors. 

c. Hybrid Mode Shifting Control 

HEVs and PHEVs can run in different driving modes, among which typical modes are electric only, engine only, hybrid/electric assist, battery charging and regenerative braking. Shifts are made among these driving modes according to the vehicle and road conditions. 

Similar to gear shifting in conventional automotive transmissions, the mode transition in hybrid transmissions may result in negative customer perception of riding comfort and drivability if it is improperly controlled. 

Engine start during mode transition is a major challenge for HEVs and PHEVs in terms of achieving good riding comfort. 

Some add-on hybrid transmissions retain a torque converter and improve their torsional damper to reduce the engine torque fluctuation from electric driving mode to hybrid driving mode. In control strategies, it is important to coordinate the engine torque, EM torque and clutch torque properly and precisely. 

Xu proposed different engine-start control strategies with respect to riding comfort or a quick response under different starting conditions. To realize the smooth and fast engine start of a P2 PHEV, Yang proposed a hierarchical mode transition control method based on a robust H∞ controller. 

Chen developed a model reference controller with which to coordinate the engine, EM and clutch torque during mode transition for a series–parallel HEV. Zhao developed a multistage optimal control strategy to determine the engine torque and clutch torque during mode transition. 

Therein, a sliding mode controller with anti-interference ability was designed to control the engine speed following the reference trajectory. Additionally, the model used to calculate feedforward control and H∞ robust feedback control was applied in the clutch synchronization phase. 

Kum investigated theoretical performance limits and corresponding optimal control strategies that achieve a trade-off between drivability and a quick engine start. 

The results indicate that the optimal engine-start control strategy should choose a proper torque reserve and a corresponding clutch pressure that balances the engine-start time and torque responsiveness depending on the vehicle state and driver input. 

It is noted that the engine-start performance of P2 hybrid transmission depends on the control of the disconnect clutch. Because the EM can provide a rapid torque response, it is precisely adjusted for both torque compensation and vehicle driving during mode transition. 

For hybrid transmissions, such as THS and Voltec-II, there is no disconnect clutch. The engine can be directly cranked using the EM. Factors affecting the riding comfort of such transmissions have been concluded. 

Proposals have been made for improving the riding comfort, e.g., varying the magnitude and frequency of the EM torque set points, the fuel ignition control and the intake air volume control. Wang designed a coordinated control strategy for a power-split hybrid transmission and verified its effectiveness by simulation and experiment. 

Active damping control based on reference output shaft speed estimation and carrier torque estimation based on transmission kinematics and dynamics were applied to mitigate driveline oscillations and suppress torque fluctuation during engine cranking. 

Zeng proposed a dynamic coordination control strategy based on model predictive control for a power-split hybrid electric bus, which is well suited to complex driving cycles. 

d. Single-Speed and Multi-speed EV Transmission

The EV configuration determines the structure of the electric propulsion system and transmission. There are four typical EV configurations considering variations of the powertrain as seen in Fig. 16, and any other EV configuration can be evolved from them. 

This section introduces the latest developments of EV transmission technologies in the central drive layout.

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