1 Introduction

With the upcoming petroleum shortage and greenhouse gas emission restrict, EVs become an inevitable solution. Variable transmission enables EVS with both rapid acceleration and high speed and is helpful for cycle life improvement of motor and inverter. Comparing to Automatic Transmission (AT), Continuously Variable Transmission (CVT), Automatic Mechanical Transmission (AMT) is of high efficiency, low cost and manufacturing convenience. So equipment of AMT with battery EVs has been a noticeable research focus.

Except the advantages and convenience mentioned above, there are emerging challenges with AMT control for EVs. Good control strategy should be designed to take comprehensive consideration of acceleration performance, energy efficiency and ride comfort. Control strategy development challenges are focused on gear shifting, driver intention recognition, driving cycle identification and frequent gearshift suppression. They are worthy of studying.

In this chapter, V-Mode of automotive controller development method is used. Firstly, the topology structure of EV was analyzed, and then the control strategy including shift schedule, driver’s intention interpretation, driving cycle recognition and frequent gearshift suppression was systematically researched and modeled with SIMULINK. After testing with Model-In-Loop (MIL) and Hardware-In-Loop (HIL), the control strategy model was interpreted to C codes by means of automatic generating of code download into real control unit and verified in vehicle test.

2 The Constitution of Pure EV AMT Transmission System

Pure EV is one kind of new energy vehicle. In this chapter, the transmission system comprises of driving motor, power battery, battery charger and AMT gearbox. The clutch was taken away for the high performance of motor speed. The output characteristics are completely different between engine and motor. Motor could output a constant torque at low speed and constant power at high speed, and has a wider range for driving, so the gears are reduced from six files to three files in the AMT transmission. The power train is detailed in Fig. 1. The key parameters are shown in Table 1.

Fig. 1
figure 1

The power-train system in pure EV

Full size image
Table 1 Vehicle-related parameters
Full size table

3 Establishment of AMT Control Strategy

The research on AMT control strategy is the key technology in AMT development. A good control strategy can imitate car driving by a skillful driver. In this case, the car could be more efficient, comfortable and safety. The development of AMT control strategy includes shift schedules, driver intention recognition, road identification, frequency shift suppression and so on [1].

3.1 Shift Schedule

Shift schedule interprets when the gear shifting will be executed based on different control parameters. Shift schedule directly influences the performance of AMT and is the key technology in the control strategy development.

The traditional shift schedule can be divided into single parameter, the two-parameter and three-parameter shift schedule, based on the different control parameters. The single-parameter shift schedule takes the vehicle speed as the only control parameter with no consideration to both the energy efficiency and power performance. Two-parameter shift schedule is based on accelerator pedal opening and vehicle speed, takes consideration to both the energy efficiency and power performance and is widely used currently. Three-parameter shift schedule is based on speed, acceleration and accelerate pedal opening, well reflects, but it is too complicated to use. The two-parameter shift schedule is currently used in AMT control strategy development for EVs. The shift schedule can be divided into dynamic shift schedule and fuel economy shift schedule.

3.1.1 Dynamic Shift Schedule

The shift points based on dynamic shift schedule are the intersections of the profiles, which represent the driving torques of the motor with different gears, as shown in Fig. 2. The optimum shift point can be calculated using the vehicle’s dynamic equation.

$$ F_{t} = F_{R} + F_{i} + F_{j} $$
(1)
$$ F_{t} = \frac{{T_{e} i_{f} i_{g} \eta_{T} }}{r} $$
(2)

Where,

Te:

is the motor output torque

if:

is differential mechanism transmission ratio

ig:

is the gearbox transmission ratio

nT:

is the transmission efficiency

r:

is the radius of driving wheel

FR:

is the rolling resistance, which can be calculated as (3)

$$ F_{R} = mgf\cos \alpha $$
(3)

Where,

m:

is the curb weight

f:

is the rolling resistance coefficient

Fi:

is the hill climbing resistance, which can be calculated as (4)

$$ F_{i} = mg\sin \alpha $$
(4)
Fj:

is the acceleration resistance, which can be calculated as (5)

$$ F_{j} = \delta m\mathop v\limits^{.} $$
(5)

Where, \( \delta \) is increase coefficient of vehicle rotating mass

Fig. 2
figure 2

The motor driving force curve in different gears

Full size image

Combining with (2)–(5), (1) will be described as (6)

$$ \frac{{T_{e} i_{f} i_{g} \eta_{T} }}{r} = mgf\cos \alpha + mg\sin \alpha + \delta_{{m\mathop v\limits^{.} }} $$
(6)

With air resistance being taken into account, F w should be added onto the right in Eq. (6). F w can be calculated as the following

$$ F_{w} = {{C_{D} A\rho v^{2} } \mathord{\left/ {\vphantom {{C_{D} A\rho v^{2} } 2}} \right. \kern-0pt} 2} $$
(7)

Where,

Fw:

is air resistance

CD:

is the coefficient of air resistance

A:

is the vehicle front area

p:

is the air density

v:

is the vehicle speed

Motor driving characteristics with different accelerator pedal opening is related to motor control strategies and the driver request. In this chapter, the diver request is interpreted as a power curve linear with the accelerator opening. So if the air resistance and ground resistance are ignored, the two-parameter power shift schedule can be simplified as that shown in Fig. 3.

Fig. 3
figure 3

Two-parameter power shift rule

Full size image

3.1.2 Fuel Economy Shift Schedule

The principles of the dynamic and fuel economy shift schedule are similar. Theoretically motor has a broad driving range, which can meet the vehicle requests at different speed. Figure 4 illustrates the motor efficiency distribution. Each accelerator opening relates to a driving efficiency curve. The shift points based on fuel economy shift schedule are the intersections of the profiles, which represent the energy efficiency of the motor with different gears.

Fig. 4
figure 4

Driving efficiency curve

Full size image

3.2 Identification of the Driver Intention

Identification of the driver request is key for a good control strategy. The driver intentions of starting, accelerating, decelerating, braking, stopping are distinguished through accelerator pedal, vehicle speed, brake pedal, cruising handle position and key signals.

Equipped with AMT, EVs could start with gear meshing because the motor performance is much better than the engine at low speed. The identification of vehicle starting is mainly concentrated on accelerator opening and the rate of pedal change. The start is divided into fast start, normal start and slow start. The key point is that how to calculate the l torque request for the motor.

The process of acceleration and deceleration is identified by the opening and the changing rate of the accelerator pedal, which includes rapid accelerating, slow accelerating, rapid decelerating, and slow decelerating. The control strategy is related to the motor torque management and AMT gear shift control.

The process of braking is identified by the opening and the changing rate of brake pedal. The control strategy is also related to the motor torque management and AMT gear change control [2, 3].

3.3 Identification and Control of the Vehicle Driving Conditions

Vehicle driving conditions can be divided into downhill, uphill and normal driving. It could be identified by the speed and the accelerator opening though fuzzy reasoning as shown in Fig. 5.

Fig. 5
figure 5

Driving conditions partition

Full size image

In Fig. 5, there are three parts, respectively representing uphill, downhill and flat road driving. The distinction boundary between these three parts is influenced by many factors. E.g. the distinction line between uphill and flat road driving is influenced by resistance of the road, acceleration, brake pedal opening, and the throttle delay. So it needs to be calibrated. Figure 6 shows the recognition logic of these three parts.

Fig. 6
figure 6

Judgment process

Full size image

Battery SOC low condition: The judgment of these conditions is relatively simple, mainly decided by the battery SOC. When the SOC is less than a certain threshold value, the vehicle works in the battery protecting mode, the judge logic and control strategy shown in Fig. 7.

Fig. 7
figure 7

Battery SOC low condition judge logic

Full size image

Brake condition: Braking condition is recognized by the brake pedal; it is divided into ordinary brake and emergency brake. It is recognized by the changing rate and the opening of the brake pedal. Here is called emergency brake if brake pedal opening >C1 and the brake pedal changing rate >C2. Only if the brake pedal opening becomes zero, the emergency brake can be cancelled. C1, C2 are the constants to be calibrated. Normal brake condition is judged by the brake opening, zero or not.

Fault conditions: Fault condition is divided into sensor’s failure and actuator’s failure. And these faults are divided into five levels for the different effects; different control strategies are developed for different fault levels. E.g. when the car is in fifth fault level, it must be powered down quickly.

Cruise condition: The judgments of the cruise condition are present gear, vehicle speed and the driver’s intentions-cruising key. When the vehicle is running at the speed designed for cruise condition, and if the present gear is the highest gear and the driver has pressed down the cruise key, then the vehicle is driven into cruise condition. The judge strategy is shown in Fig. 8.

Fig. 8
figure 8

Cruise condition judgment

Full size image

Energy regenerative condition: Energy regenerative condition has two trigger conditions: one is the driver depresses the brake pedal which belongs to be an ordinary brake and the other is the vehicle speed is too high;

3.4 Frequent Shift Suppression

Vehicle running environment is complex, and the drivers have different driving skills. Shift schedule with two parameters is determined by the accelerator and vehicle speed. So when the accelerator changes frequently or the vehicle speed changes fast, it may lead to the gear up and down frequently, which is an abnormal shifting and harmful to the vehicle to be avoided.

There are several control strategies for frequent shifting inhibition. In this chapter, the accelerator pedal deactivation and shift-delay strategy is proposed, according to abnormal shifting frequency caused by driver request and the road environment [4].

3.4.1 Accelerator Pedal Deactivation Strategy

Accelerator pedal deactivation strategy is to turn the abrupt changes of accelerator pedal opening into gentle changes, to make it “bluntness”. The accelerator pedal signal will be amended to change slowly and smoothly with the strategy. And the frequent shifting could be avoided based on the “passive” accelerator pedal opening signal, as shown in Fig. 9.

Fig. 9
figure 9

Accelerator pedal passive strategy

Full size image

3.4.2 The Strategy of Shift Delay and Shift Holding

There will be abnormal frequent shifting if the vehicle is on crooked roads or uphill with normal shift schedule.

In that case, it may be so dangerous that the vehicle loss driving power to slide down.

In this chapter, shift delay and shift holding strategies are used to avoid frequent shifting.

4 Modelling and Simulation

4.1 Building MATLAB/SIMULINK Simulation Model

In order to check the developed control strategies, the simulation model is built based on matlab/Simulink, which can be divided into three parts: input signal simulation, control strategy part and vehicle dynamic model. Figure 10 shows the control strategy part, it contains condition judging and control strategy.

Fig. 10
figure 10

MATLAB/Simulink simulation model

Full size image

4.2 Simulation

Simulation tests include starting strategy,gearing process control strategy,automatic shift logic, driver intention identification and so on. In this chapter, the simulation results of AMT control and motor control on braking condition are illustrated. The brake condition can be divided into two parts: normal brake with energy recovery and hard brake without energy recovery.

4.2.1 Normal Brake with Energy Recuperated

The braking energy recycle strategy is used to control that when energy is recuperated and how much energy is to be recuperated Fig. 11 shows the simulation result. The first chart shows the changing of the vehicle speed, gear and trigger of the energy recycle. The second chart shows the change of the accelerator and the brake pedal. Within the first 300 s, the gear is shifted from the first file up to the third file, and the energy recycle is triggered when the brake pedal is pressed and the vehicle decelerates. When the speed drops to some value, the energy recycle ends and the gear shifts from the third file down to the first file.

Fig. 11
figure 11

Simulation of normal brake condition strategy

Full size image

4.2.2 Hard Brake Condition

The strategy of the hard brake condition is mainly about gear decision-making. The simulation result of the strategy is shown in the Fig. 12. The first chart shows the changing of the vehicle speed, gear and trigger of the energy recycle signal. The second chart shows the change of the accelerator pedal and the brake pedal.

Fig. 12
figure 12

Simulation of hard brake condition strategy

Full size image

At the beginning of the brake pedal depression, it’s recognized as a normal brake condition with energy recycle. With the increasing of brake pedal opening, it is recognized as hard brake condition with energy recycle cancelled and gear preserved. Only if the vehicle decelerates to a low speed, the gear will be shifted down to the first file with the braking cancelled.

5 Vehicle Test Results

Figure 13 shows the test result of the AMT control strategy on actual vehicles.

Fig. 13
figure 13

The result of the automatic gearing strategy

Full size image

The first chart shows the aim gear, the second chart shows motor torque (Nm), the third chart shows the opening of the accelerate pedal (%), the forth chart shows vehicle speed (km/h), the last shows the present gear. The graphs show that the vehicle can shift automatically.

Figures 14 and 15 show the result of the control strategy of shift process.

Fig. 14
figure 14

Gearing process control from second to third file

Full size image
Fig. 15
figure 15

Gearing process control from second to third file

Full size image

The time between the two vertical lines is shift time, which is less than one second as shown.

The second chart shows the output shaft speed (r/min), whose change is no more than 50 r/min, as shown in Fig. 15.

6 Conclusions

Driver intention recognition method proposed in the article can identify the driver intentions effectively, fuzzy reasoning method, which is used to recognize vehicle running environment, can identify some specific road information, frequency gearshift suppression control strategy can reduce the unnecessary gearshift effectively when running.