Development Trends of Transmissions for Hybrid Electric Vehicles Using an Optimized Energy Management Strategy
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Energy conservation and emissions reduction have become increasingly significant for automobiles due to the severity of the current energy situation. Hybrid electric vehicle (HEV) technology is one of the most promising solutions. This study investigated the total efficiency of a HEV powertrain. To improve the total efficiency, the engine should be regulated to work at its highest efficiency and drive the wheels directly as much as possible. To accomplish this, we developed an energy management strategy based on the direct drive area (DDA) of the engine’s efficiency map. Several typical HEV models were built to compare the fuel consumption using DDA and rule-based strategies. Furthermore, the function of the HEV transmission system with DDA was considered. The transmission in a HEV should regulate the engine to work at its highest efficiency as much as possible, which is rather different than the regulation in an internal combustion engine vehicle. The functional change may lead to transmission systems with fewer gears but optimal gear ratios. If this trend is realized, the manufacturing cost of HEVs could be largely reduced.
KeywordsHEV Direct drive area Energy management Transmission cost reduction
Direct drive area
Continuously variable transmission
Hybrid electric vehicle
Internal combustion engine
Internal combustion engine vehicle
New European driving cycle
- P2 HEV
State of charge
- SP HEV
Front face area
Rolling resistance coefficient
Rotary inertia of wheel
Rotary inertia of engine
Transmission gear ratio
Gear ratio of final drive
Vehicle running speed
Mechanical efficiency of power system
Transportation demands are increasing as modern cities continue to grow quickly [1, 2, 3, 4]. This tendency leads to increased pollution, energy shortages, and other serious problems [5, 6]. Tailpipe emissions from vehicles must be controlled to enable sustainable development [7, 8, 9, 10, 11]. Efforts have been made in countries across the world to address the issues of large energy consumption in the transportation sector [12, 13, 14], including limiting transportation activity, restricting the purchase of automobiles, enacting strict emission regulations, improving vehicle fuel efficiency, and developing new energy sources for vehicles [15, 16]. Among the suggested solutions, the development of new energy sources is considered one of the most promising and practical methods [17, 18, 19]. Researchers and automotive manufactures have therefore committed a great effort to progress in this field.
A hybrid electric vehicle (HEV) is a complex system that integrates electronic, mechanical, chemical, and thermodynamic technologies. When a HEV is in motion, power and information are being transferred and transformed by various flows. The potential for HEVs to save energy and reduce emissions is determined by the means by which components are connected mechanically and the management of energy transfers between the internal combustion engine (ICE) and electric motor. The HEV onboard generator can charge the battery and recover energy by regenerative braking, allowing the battery to sustain an advantageous state of charge (SOC). A HEV that uses a smaller, more efficient ICE can achieve better fuel economy. The ICE can also operate within its most efficient operating area most of the time and can be switched off when necessary.
By combining the advantages of ICEs and electric vehicles (EVs), HEVs are quite promising for vehicle technology development in the short to mid term . Lave and MacLean  compared a hybrid car to an ICE car and found that HEVs are not only effective for improving fuel economy and reducing emissions, but also, with gasoline price rising in the future, significantly reducing vehicle operating costs. Nordelof et al.  investigated the usefulness of different types of life-cycle assessments of HEVs and EVs to provide an overview of the environmental impacts. Hannan et al.  made a comprehensive review in the field of HEVs, concluding that existing technologies are capable of enabling good HEV performance, but that the reliability and “intelligence” of HEV systems are still somewhat inadequate. Cummings et al.  investigated the effect of sensitivity for sensing and prediction in vehicle fuel economy improvements. Morais et al.  presented distributed energy resource management using plug-in HEVs as a fuel-shifting demand response resource, which scheduled the EV’s charging and discharging processes to avoiding network congestion. Chen et al.  investigated the influence of electrification on transportation and road systems. Lave and MacLean  made an environmental-economic evaluation between the HEV Toyota Prius and its ICE vehicle (ICEV) edition, the Corolla, pointing out that with fuel prices rising, the HEV would have significantly more market share in the future.
Different types of HEVs are classified by their degree of hybridization or their mechanical configuration. The main challenge for HEVs is splitting the power in an optimal way while delivering the desired performance under system constraints [27, 28]. Specifically, an energy management system is needed to select or combine the power sources for driving the vehicle [29, 30, 31]. Many different mechanical designs and energy management strategies have previously been presented by researchers using simulations and road tests [32, 33, 34, 35]. Researchers have made great progress in regard to HEV general configurations, power electronic components [32, 33], and energy management strategies [34, 35]. The technology has developed rapidly and seen many breakthroughs. Morteza and Mehdi  developed a new energy management strategy for power splitting in HEVs using a multi-input fuzzy logic controller to further improve their fuel economy, tailpipe emissions, and performance in various driving cycles. Finesso et al.  applied an equivalent consumption minimization strategy to identify the optimal control strategy for a parallel HEV (P2 HEV). Li et al.  introduced a downshift strategy, and their hardware-in-the-loop simulation showed that this strategy can improve the energy conservation of HEV regenerative braking by 10%–32%. Hannan et al.  studied a control system for a multi-energy source HEV. The control algorithm was developed to fulfill various driving conditions, and the simulation model  was built under the ECE-47 driving cycle. Their results showed that their multi-source control strategy could be efficient and conserve energy.
However, most research on the topic of HEVs is based on an architecture that uses traditional transmissions. Because the transmission system in a HEV should have functions different from those in an ICEV, its development direction should be different from that for ICEVs. In this context, this paper discusses the future direction of HEV transmission development.
2 Modeling of Hybrid Electric Vehicles
2.1 Base Parameters
The New European Driving Cycle (NEDC) was applied to the calculation. The NEDC was established by the European Union and is applied in China. In the NEDC cycle, the vehicle is operated according to a given velocity curve. The total cycle lasts for 1200 s and has a top speed of 120 km/h. With vehicle velocity as input data, the force and power needed in a NEDC cycle for a typical car are obtained. The total energy consumption in a NEDC cycle is obtained by integration of the power data.
Key parameters of the vehicle
2.2 Rule-Based Energy Management
The existing energy management strategies for HEVs can be mainly classified into rule-based and optimization-based management. Both types have been extensively studied. The researches have covered various aspects of these strategies, including the state of the art of energy management strategy, general formalization of the energy management problem, and characteristics and control effects of different strategies [32, 33, 34, 35, 36, 37, 38, 39]. In an industrial application, rule-based strategies are more widespread. Although they cannot obtain an optimum solution, they are easy to implement because they have fixed rules. Thus, rule-based strategies have been successfully used in commercial HEVs, and they provided the baseline for this study.
The logic flow of the rule-based strategy for P2 HEVs used in this study is as follows. First, the demand power P, demand torque Tr, and acceleration acc are obtained as base demands. Second, the torques of best efficiency, motor working area, and maximum torque of the engine at a certain speed are determined. Third, the charging or discharging work mode is determined using the battery SOC. Finally, the demand engine and motor torque and battery charge or discharge state are obtained.
2.3 Fuel Consumption Baselines
With the necessary data and energy management strategy ready, the baseline ICEV and HEV models could be created. The NEDC condition was applied to calculate the FC, as implemented by the FC testing and evaluation provisions of the China National Standard.
FC values of baseline models
FC (L/100 km)
ICEV without trans.
ICEV with trans.
ICEV with CVT
P2 HEV without trans.
P2 HEV with trans.
3 Direct Drive Area (DDA) Energy Management
3.1 Improving Total Efficiency
A HEV is driven by an ICE in combination with one or more electric motors. A battery package is connected to the motors as a secondary system to provide power to them. Reducing the FC of a HEV is equivalent to improving the efficiency of the HEV powertrain system, especially the working efficiency of the ICE. As the high-efficiency area of an engine efficiency map is rather small, engine speed/torque regulation is necessary to keep it working in this area.
However, regulating the engine working points to remain only at the best efficiency point is not the best solution. This regulation is usually done by motor torque adjustment. When the engine working point is regulated to the best efficiency point or line, the energy loss of motor and battery efficiency is inevitable. If the torque demand is less than the engine’s best torque at a certain speed, the generator works and the energy is stored in the battery. Otherwise, if the torque demand is more than the engine’s best torque, the motor works to provide the torque needed. Neither approach will cause energy loss in the motor drive or battery.
In the DDA strategy, the engine will directly drive the wheels in the DDA, rather than being regulated to the best efficiency point. In this way, energy loss in the motor and battery is avoided. Actually, similar results have been obtained using a dynamic programming (DP) method . The working points regulated by the DP method are usually distributed near the DDA, and the results show good FC reduction. But the DP method can only be used when the whole working condition is already known, and the calculation speed is rather slow. Thus, it is not used in industrial applications. While the DDA method is a rule-based strategy, the DDA is determined in advance. During the driving cycle, the working point of the torque and speed is determined. If it is within the DDA, the engine directly drives the wheels; otherwise, the working point is regulated to the best efficiency point, with the motor assisting the power output.
3.2 Application of DDA Method
4 HEV Transmission Improvement Tendency
4.1 Functions of HEV Transmission
Application of the DDA method changes the function of the transmission in a HEV. In an ICEV, the function of the transmission is to regulate the working point as close as possible to the best efficiency line of the engine at a given power. This means that more gears in a transmission result in better regulation. But more gears mean higher costs. Thus, most commercial transmissions have five or six gears. In theory, the CVT could achieve an infinite number of gears to realize the best efficiency point under any condition. However, the transmission efficiency of CVTs is rather low due to the application of a torque converter. Transmissions in ICEVs have already been thoroughly addressed along with the development of vehicles.
As the engine working points regulated by the transmission follow a hyperbola, different operating profiles are revealed at higher and lower speeds. When regulating the higher-speed working points to lower speed, the torque will increase correspondingly to ensure the same power output. Because most high-speed conditions are associated with lower torque demands, points in this area could be regulated into the DDA with a high probability of better efficiency.
However, when regulating a lower-speed point to high speed, the torque decreases. If the original torque is low, then the regulated torque decreases and might fall out of DDA. In this case, the hybrid mode will be engaged. If the torque is too low, the electric mode becomes active and the vehicle is driven only by the motor. Otherwise, the hybrid mode is active, and the driving point is forced to the best torque/speed ratio that drives the wheels while charging the battery. Meanwhile, the battery SOC is also considered to decide which mode to select. In either case, the objective is to make the total efficiency higher than the original (unregulated) efficiency point. For example, some driving points at lower speeds have higher torque. In this case, these points could probably be regulated into the DDA to improve total efficiency.
The above considerations indicate that the future HEV transmission development trends might be as follows. First, as the regulation target is an interval rather than a point, more gears are not necessary for HEVs. Second, to regulate a wide speed range into a narrow speed interval, transmission ratios must be redesigned.
4.2 Transmission Improvement
Verification models were built to support evaluation of the two major directions of HEV transmission development. The SP HEV system could be considered as an electric CVT between the engine and wheels. This is because all the points outside the DDA can be regulated to the best efficiency point (2100 rpm/100 N m), just like a continuous speed change. In contrast, in the P2 HEV system, the transmission changes speed in steps, and speed intervals can be achieved only by regulating the efficiency points. From the perspective of cost, it is suggested that a step-changing transmission is preferable when applying the DDA method. Recall that the FC value of an SP HEV with transmission is 4.06 L/100 km, and that of a P2 HEV with transmission is 4.09 L/100 km. The slight change comes from the regulated points that are outside DDA. In the SP HEV system, these points are regulated to the best (40%) efficiency point. In the P2 HEV system, the points are along the line nearest the best point, with a slightly lower average engine efficiency. Note that the P2 HEV system is constructed with fewer components, that is, engine, motor, and transmission. The SP HEV system with transmission has these components plus an additional generator. It should be noted that the commercial SP HEV cars of Honda have no transmission, as shown in Fig. 4. As the P2 HEV has a better cost performance, we further studied transmission applications based on P2 HEV systems.
The results presented above support the utility of the HEV transmission development trends that we have proposed. With fewer gears but optimal ratios, the cost of HEV transmissions could be reduced and help increase HEV penetration in the vehicle market.
This paper described how the future function of HEV transmissions will be different, which will regulate engine speed into a certain speed interval, rather than to the best efficiency point for a given power. Development trends of HEV transmissions based on this new function were predicted, that is, that fewer gears will be used in HEV transmissions, but the gear ratios will be optimized. This conclusion is based on several HEV models, an energy management strategy considering total efficiency, and an engine working point distribution analysis. The presented DDA method made the engine drive the wheels directly in the high-efficiency area. In contrast, the rule-based strategies forced the engine to work along the best efficiency line in the efficiency map. The DDA method was verified by applying it to different HEV models. With fewer transmission gears, the total cost of an HEV will be reduced, which is beneficial for increasing market share.
This study is sponsored by the National Natural Science Foundation of China (71403142, 71774100, 71690241), Young Elite Scientists Sponsorship Program of the Chinese Association for Science and Technology (YESS20160140), and Beijing Natural Science Foundation (9162008).
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